CN114780908A - Data processing method, device, equipment and computer readable storage medium - Google Patents
Data processing method, device, equipment and computer readable storage medium Download PDFInfo
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Abstract
The invention discloses a data processing method, a device, equipment and a computer readable storage medium, wherein the data processing method comprises the following steps: the method for acquiring communication transmission data, performing data analysis on the communication transmission data to obtain communication evaluation data, and performing data analysis on the communication transmission data to obtain communication evaluation data comprises the following steps: the method comprises the steps of obtaining sequence data of communication transmission data, carrying out linear operation conversion processing on the sequence data to obtain initial solution space data, carrying out summarizing processing on the initial solution space data to obtain target solution space data, obtaining intersection data in the target solution space data to obtain intersection solution space data, and carrying out solution processing on the intersection solution space data according to a preset solution algorithm to obtain communication evaluation data. The invention can reduce the calculation amount of the solution sequence data.
Description
Technical Field
The present invention relates to the field of computer communication technologies, and in particular, to a data processing method, apparatus, device, and computer-readable storage medium.
Background
At present, in the world of everything interconnection, new technologies such as 5G, big data, artificial intelligence and the like bring innovation vitality to the Internet of Things (Internet of Things, IoT), the Internet of Things has the characteristics of large connection scale and various access modes, and the boundary between the digital world and the physical boundary is gradually ablated. 5G communication is also an important field of national development at present, technologies such as communication coding, communication channel estimation, synchronization and the like are increasingly developed, wherein one of the problems in the communication field is that various applications more or less relate to the construction of sequences, and the construction of sequences mostly relates to the solution of a multivariate nonlinear equation set.
In the related art, the solution of the multivariate nonlinear equation by a computer adopts a direct numerical trial method, uses an exhaustive mode and takes decimal single number as a basis to try all solution data until the final solution data is obtained. The algorithm is huge in calculation amount for a multi-element nonlinear equation, and the calculation amount is increased along with the increase of the sequence length.
Disclosure of Invention
The present invention is directed to solving at least one of the problems of the prior art. Therefore, the invention provides a data processing method which can reduce the calculation amount of solving the sequence data.
The invention also provides a data processing device.
The invention also provides data processing equipment.
The invention also provides a computer readable storage medium.
In a first aspect, an embodiment of the present invention provides a data processing method, including:
acquiring communication transmission data;
performing data analysis on the communication transmission data to obtain communication evaluation data;
the performing data analysis on the communication transmission data to obtain communication evaluation data includes:
acquiring sequence data of the communication transmission data;
performing linear operation conversion processing on the sequence data to obtain initial solution space data;
summarizing the initial solution space data to obtain target solution space data;
acquiring intersection data in the target solution space data to obtain intersection solution space data;
and performing solution processing on the intersection solution space data according to a preset solution algorithm to obtain the communication evaluation data.
The data processing method of the embodiment of the invention at least has the following beneficial effects: carrying out data analysis on the acquired communication transmission data, wherein the data analysis comprises the following steps: the method comprises the steps of obtaining a plurality of sequence data of communication transmission data, carrying out linear operation conversion processing on the sequence data to obtain initial solution space data of each sequence data, converting the sequence data into linearity, then carrying out summarization processing on the initial solution space data to obtain a set of the plurality of initial solution space data, namely target solution space data of each sequence data, then obtaining data of intersection of each target solution space data to obtain intersection solution space data, and finally carrying out solution processing on the intersection solution space data according to a preset solution algorithm to obtain communication evaluation data, so that the calculation amount for solving the sequence data can be reduced.
According to another embodiment of the present invention, a data processing method, performing linear operation transformation processing on the sequence data to obtain initial solution space data, includes:
acquiring coefficient matrix data corresponding to the sequence data;
solving by taking the sum of the coefficient matrix data as zero to obtain first solution space data, wherein the first solution space data comprises a plurality of solution base data;
adding any two pieces of base data between the plurality of pieces of first solution space data, and/or multiplying the base data by a preset scalar to obtain second solution space data;
determining the initial solution space data according to the first solution space data and the second solution space data.
According to another embodiment of the present invention, the acquiring coefficient matrix data corresponding to the sequence data includes:
expressing the sequence data by a preset linear equation expression to obtain a target linear equation, wherein the preset linear equation expression is formed by combining preset parameters, a coefficient matrix and transposed data of the preset parameters;
and acquiring the coefficient matrix in the target linear equation to obtain the coefficient matrix data.
According to another embodiment of the present invention, the summarizing the initial solution space data to obtain target solution space data includes:
acquiring coefficient matrix data corresponding to the sequence data;
performing transposition processing on the coefficient matrix data to obtain transposition matrix data;
solving processing is carried out by taking the sum of the transposed matrix data as zero to obtain third solution space data;
and summarizing the third solution space data and the initial solution space data to obtain the target solution space data.
According to another embodiment of the present invention, the data processing method for performing summary processing on the initial solution space data to obtain target solution space data further includes:
performing corresponding processing on the coefficient matrix data according to a preset processing rule to obtain conversion matrix data;
solving is carried out by taking the sum of the conversion matrix data as zero to obtain fourth solution space data;
and summarizing the third solution space data, the fourth solution space data and the initial solution space data to obtain the target solution space data.
According to another embodiment of the data processing method, the obtaining intersection data in the target solution space data to obtain intersection solution space data includes:
acquiring two linearly related target solution space data;
performing column direction splicing processing on the two target solution space data to obtain corresponding spliced solution space data;
transposing the splicing solution space data to obtain transposed solution space data;
intercepting and transposing the preset columns of the spatial data of the transposing solution to obtain intercepted spatial data of the solution;
and multiplying the target solution space data and the intercepted solution space data and solving by taking the sum as zero so as to obtain the intersection solution space data.
According to another embodiment of the data processing method, the performing solution processing on the intersection solution space data according to a preset solution algorithm to obtain the communication evaluation data includes:
acquiring combined solution space data according to the intersection solution space data;
and solving the combined solution space data according to the preset solving algorithm to obtain the communication evaluation data.
In a second aspect, an embodiment of the present invention provides a data processing apparatus, including:
the acquisition module is used for acquiring communication transmission data;
the analysis module is used for carrying out data analysis on the communication transmission data to obtain communication evaluation data;
the analysis module includes:
an acquisition unit configured to acquire sequence data of the communication transmission data;
the conversion unit is used for carrying out linear operation conversion processing on the sequence data to obtain initial solution space data;
the summarizing unit is used for summarizing the initial solution space data to obtain target solution space data;
the intersection unit is used for acquiring intersection data in the target solution space data to obtain intersection solution space data;
and the solving unit is used for solving the intersection solution space data according to a preset solving algorithm so as to obtain the communication evaluation data.
The data processing device of the embodiment of the invention at least has the following beneficial effects: the analysis module carries out data analysis to the communication transmission data that the acquisition module obtained, and the acquisition module includes: the acquisition unit acquires a plurality of sequence data of communication transmission data, the conversion unit performs linear operation conversion processing on the sequence data to obtain initial solution space data of each sequence data, the sequence data can be converted into linearity, then the collection unit performs collection processing on the initial solution space data to obtain a set of a plurality of initial solution space data, namely target solution space data of each sequence data, then the intersection unit acquires intersection data of each target solution space data to obtain intersection solution space data, and finally the solving unit performs solution processing on the intersection solution space data according to a preset solving algorithm to obtain communication evaluation data, and calculation amount of solving the sequence data can be reduced.
In a third aspect, an embodiment of the present invention provides a data processing apparatus, including:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the data processing method of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium storing computer-executable instructions for causing a computer to perform the data processing method according to the first aspect.
Additional features and advantages of the present application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the present application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
FIG. 1 is a flow chart illustrating a data processing method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating one embodiment of step S200 of FIG. 1;
FIG. 3 is a flowchart illustrating one embodiment of step S220 in FIG. 2;
FIG. 4 is a flowchart illustrating one embodiment of step S221 in FIG. 3;
FIG. 5 is a flowchart illustrating one embodiment of step S230 of FIG. 2;
FIG. 6 is a flowchart illustrating another embodiment of step S230 shown in FIG. 2;
FIG. 7 is a flowchart illustrating one embodiment of step S240 in FIG. 2;
FIG. 8 is a flowchart illustrating one embodiment of step S250 of FIG. 2;
FIG. 9 is a block diagram of an embodiment of a data processing apparatus;
description of the drawings:
the system comprises an acquisition module 100 and an analysis module 200;
the system comprises an acquisition unit 210, a conversion unit 220, a summary unit 230, an intersection unit 240 and a solving unit 250.
Detailed Description
The idea of the invention and the resulting technical effects will be clearly and completely described below in connection with the embodiments, so that the objects, features and effects of the invention can be fully understood. It is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments, and those skilled in the art can obtain other embodiments without inventive effort based on the embodiments of the present invention, and all embodiments are within the protection scope of the present invention.
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and do not limit the invention.
It should be noted that although functional block divisions are provided in the system drawings and logical orders are shown in the flowcharts, in some cases, the steps shown and described may be performed in different orders than the block divisions in the systems or in the flowcharts.
In the description of the present invention, unless otherwise specifically limited, terms such as set, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention by combining the specific contents of the technical solutions.
In the description of the embodiments of the present invention, if "a number" is referred to, it means one or more, if "a plurality" is referred to, it means two or more, if "greater than", "less than" or "more than" is referred to, it is understood that the number is not included, and if "greater than", "lower" or "inner" is referred to, it is understood that the number is included. If reference is made to "first" or "second", this should be understood to distinguish between features and not to indicate or imply relative importance or to implicitly indicate the number of indicated features or to implicitly indicate the precedence of the indicated features.
Referring to fig. 1, a flowchart of a data processing method in an embodiment of the present invention is shown. In addition, the present embodiment discloses a data processing method, which specifically includes, but is not limited to, including step S100 to step S200.
Step S100, communication transmission data are obtained;
in step S100, transmission data subjected to spatial matrix communication coding is acquired to obtain communication transmission data.
And step S200, carrying out data analysis on the communication transmission data to obtain communication evaluation data.
In step S200, a correlation coefficient of the communication transmission data is obtained, and the correlation coefficient is solved and analyzed to obtain communication evaluation data.
By executing steps S100 to S200, the transmission data subjected to the spatial matrix communication coding is acquired to obtain communication transmission data. And solving and analyzing the correlation coefficient data of the communication transmission data to obtain communication evaluation data.
Referring to fig. 2, a flowchart of a data processing method in the embodiment of the present invention is shown. In addition, the present embodiment discloses a data processing method, which specifically includes, but is not limited to, including step S210 to step S250.
Step S210, acquiring sequence data of communication transmission data;
in step S210, an autocorrelation equation of the communication transmission data is acquired to obtain sequence data.
It should be noted that, the present invention needs to construct the communication transmission data as perfect gaussian integer sequence data, and extract an autocorrelation equation of the communication transmission data, for example, determine the sequence data as follows:
analysis of one of the sequence data R00 shows that all the items are characterized by two,
all entries of the sequence data R11 are also characterized as quadratic,
all entries of the sequence data R21 are also characterized as quadratic,
to construct perfect gaussian integer sequence data, R00-0, R01-0, R02-0, R10-0, R11-0, R12-0, R20-0, and R21-0 are required. And R22 representing its own energy is not zero. To achieve this condition, it is necessary to solve 8 equations composed of all sequence data. Also, the sequence data R22 represents energy, naturally not equal to zero.
Step S220, carrying out linear operation conversion processing on the sequence data to obtain initial solution space data;
in step S220, a quadratic coefficient of each sequence data is extracted, and the quadratic coefficient is linearized, and the dimension of the sequence data is reduced to a linear equation system to obtain initial solution space data.
Step S230, summarizing the initial solution space data to obtain target solution space data;
in step S230, more solution space data of each sequence data is found, and the solution space data and the initial solution space data are subjected to a summary process to obtain target solution space data.
Step S240, acquiring intersection data in the target solution space data to obtain intersection solution space data;
in step S240, data with an intersection between all target solution space data is obtained to obtain intersection solution space data.
And step S250, performing solution processing on the intersection solution space data according to a preset solution algorithm to obtain communication evaluation data.
In step S250, the intersection solution space data is subjected to solution processing according to a preset solution algorithm, and an intersection solution space numerical solution is obtained, so as to obtain communication evaluation data.
By executing steps S210 to S250, first, an autocorrelation equation of communication transmission data is acquired to obtain sequence data. And then, carrying out linearization processing on the sequence data according to the quadratic coefficient of each sequence data, and reducing the dimension of the sequence data to a linear equation system to obtain initial solution space data. And secondly, solving more solution space data of each sequence data, and summarizing the solution space data and the initial solution space data to obtain target solution space data. And then, acquiring data with intersection in all the target solution space data to obtain intersection solution space data. And finally, solving the intersection solution space data according to a preset solving algorithm, and solving an intersection solution space numerical value solution to obtain communication evaluation data.
Referring to fig. 3, a flowchart of a data processing method in an embodiment of the present invention is shown. In addition, the present embodiment discloses a data processing method, which specifically includes, but is not limited to, including steps S221 to S224.
Step S221, coefficient matrix data corresponding to the sequence data is obtained;
in step S221, coefficient matrix data of respective sequence data, one for each sequence data, is acquired.
For example, the coefficient matrix data A00 of the sequence data R00 is:
step S222, solving is carried out by taking the sum of the coefficient matrix data as zero to obtain first solution space data, and a plurality of solution base data can be obtained according to the first solution space data;
in step S222, the value of each coefficient matrix data is equal to zero, and all solutions of each coefficient matrix data are solved according to a null-space solution method to obtain corresponding first solution space data, where the first solution space data includes a plurality of solution base data.
It should be noted that each line of data of the first solution space data corresponds to one solution base data.
For example: coefficient matrix data A00When equal to 0, NullSpace (A) is calculated00)：
Wherein, the solution base data corresponding to the first row is: {0,0,0,0,0,0,0,0,0,0,0,0,0, -1,0,0,0,2}.
Step S223, adding any two pieces of solution base data among the plurality of pieces of first solution space data, and/or multiplying the solution base data by a preset scalar to obtain second solution space data;
in step S223, any two pieces of solution base data of each piece of first solution space data are added to obtain a new solution base data, the new solution base data may also be obtained by multiplying a preset scalar by one piece of solution base data, and the solution base data and the new solution base data are combined to obtain the second solution space data.
It should be noted that each first solution space data generates new solution base data through the solution base data included in itself, and the new solution base data can be used for generating other new solution base data.
For example: null (Null)Space(A00) Two solution basis data of (2): {0,0,0,0,0,0,0,0,0,0,0,0, -1,0,0,0, 0,2} and {0,0,0,0,0,0,0,0, -1,0,0,1,0}, adding the two pieces of solution base data to obtain new solution base data: {0,0,0,0,0,0,0,0,0,0,0,0,0, -2,0,0,1,2}.
Step SS224 of determining initial solution space data according to the first solution space data and the second solution space data
In step S224, all the first solution space data and all the second solution space data are combined into one initial solution space data.
By executing steps S221 to S224, first, coefficient matrix data of each sequence data is acquired, and all solutions of each coefficient matrix data are solved according to a null-space solution method to obtain corresponding first solution space data, where the first solution space data includes a plurality of solution base data. Then, any two pieces of solution base data of each first solution space data are added to obtain a new solution base data, or one piece of solution base data is multiplied by a preset scalar to obtain a new solution base data, and the solution base data and the new solution base data are combined to obtain second solution space data. And finally, combining all the first solution space data and all the second solution space data into initial solution space data.
Referring to fig. 4, a flowchart of a data processing method in an embodiment of the present invention is shown. In addition, the present embodiment discloses a data processing method, which specifically includes, but is not limited to, including step S2211 to step S2212.
Step S2211, representing the sequence data by a preset linear equation expression to obtain a target linear equation, where the preset linear equation is formed by combining preset parameters, a coefficient matrix, and transposed data of the preset parameters;
in step S2211, a coefficient matrix of each sequence data is obtained, a preset parameter is preset, the preset parameter is transposed to obtain transposed data, and the preset parameter, the coefficient matrix, the transposed data, and the sequence data are expressed according to a preset linear equation expression to obtain a target linear equation.
It should be noted that the target linear equation is: the preset parameters, the coefficient matrix and the transposed data are subjected to matrix multiplication to be equal to sequence data. Wherein, a target linear equation is generated correspondingly for each sequence data.
For example: the preset parameters are as follows:
transpose the data as: xTTaking the sequence data R00 as an example, the coefficient matrix a00 of the sequence data R00 is obtained, and by combining a preset linear equation expression, a target linear equation can be obtained:
step S2212, obtain coefficient matrix in target linear equation to obtain coefficient matrix data.
In step S2212, the coefficient matrix is obtained by converting the objective linear equation to obtain coefficient matrix data.
By executing steps S2211 to S2212, a coefficient matrix of each sequence data is obtained, and a preset parameter, the coefficient matrix, the transposed data, and the sequence data are expressed according to a preset linear equation expression, so as to obtain a target linear equation. And obtaining a coefficient matrix by converting the target linear equation to obtain coefficient matrix data. To extract a quadratic coefficient of the sequence data and linearize the quadratic coefficient.
Referring to fig. 5, a flowchart of a data processing method in the embodiment of the present invention is shown. In addition, the present embodiment discloses a data processing method, which specifically includes, but is not limited to, including steps S221 to S233.
Step S231, transposing the coefficient matrix data to obtain transposed matrix data;
in step S231, the coefficient matrix data is transposed to obtain corresponding transposed matrix data.
For example: the coefficient matrix data a21 is:
the transposed matrix data of the coefficient matrix data a21 is:
step S232, solving is carried out by taking the sum of the transposed matrix data as zero to obtain third solution space data;
in step S232, the value of each transposed matrix data is equal to zero, and all solutions of each transposed matrix data are solved according to a null-space solution method, so as to obtain third solution space data.
For example: transposed matrix data A21 TThe third solution space data of (2) is:
step S233, the third solution space data and the initial solution space data are summarized to obtain target solution space data.
In step S233, the third solution space data and the initial solution space data are summarized and combined to obtain a target solution space data.
For example: the initial solution space data of the coefficient matrix data a21 is:
the target solution space data of the coefficient matrix data a21 is:
by performing steps S231 to S233, first, the coefficient matrix data is transposed to obtain corresponding transposed matrix data. Then, the value of each transposed matrix data is equal to zero, and all solutions of each transposed matrix data are solved according to a zero-space solution method to obtain third solution space data. And finally, summarizing the third solution space data and the initial solution space data, and combining to obtain target solution space data.
Referring to fig. 6, a flowchart of a data processing method in an embodiment of the present invention is shown. In addition, the present embodiment discloses a data processing method, which specifically includes, but is not limited to, including step S234 to step S236.
Step S234, the coefficient matrix data is correspondingly processed according to a preset processing rule to obtain conversion matrix data;
in step S234, a value conversion process is performed on the preset diagonal line data of the coefficient matrix data according to a preset processing rule to obtain conversion matrix data.
It should be noted that the result of adding the corresponding preset diagonal data obtained after the conversion is consistent with the result of adding the preset diagonal data obtained after the conversion.
For example: the coefficient matrix data a21 is subjected to numerical conversion processing to obtain conversion matrix data:
wherein, other non-zero data than the predetermined diagonal data, e.g. coefficient matrix data A21Has an element of 4 in the second row and the third column, has 0 diagonal data, and has an added sum of 4 diagonal data (third row and second column elements). It may cause the matrix data a to be converted21 t1The second row and third column of elements 3, and the diagonal elements (third row and second column elements) are 1, and the sum after addition is 4, the quadratic polynomial equation can also be generated. Namely: conversion matrix data A21 t1Corresponding system of preset diagonal line data of ' 1 ' and ' 3Number matrix data A21Preset diagonal line data "0" and "4", conversion matrix data a21 t1And coefficient matrix data A21The sum of the preset diagonal data of (a) is equal.
Step S235, solving is carried out by taking the sum of the conversion matrix data as zero to obtain fourth solution space data;
in step S235, the value of each conversion matrix data is made equal to zero, and all solutions of each conversion matrix data are solved according to a null-space solution to obtain fourth solution space data.
It should be noted that the fourth solution space data generated by the conversion matrix data may be equal or different, so that all solutions of the conversion matrix data can be obtained by combining the generated fourth solution space data.
Step S236, summarizing the third solution space data, the fourth solution space data, and the initial solution space data to obtain target solution space data.
In step S236, the third solution space data, the fourth solution space data, and the initial solution space data are summarized and combined to obtain a target solution space data.
By performing steps S234 to S236, first, the predetermined diagonal line data of the coefficient matrix data is subjected to a numerical value conversion process according to a predetermined processing rule to obtain conversion matrix data. Then, the value of each conversion matrix data is equal to zero, and all solutions of each conversion matrix data are solved according to a null-space solution method to obtain fourth solution space data. And summarizing the third solution space data, the fourth solution space data and the initial solution space data, and combining to obtain target solution space data.
Referring to fig. 7, a flowchart of a data processing method in an embodiment of the present invention is shown. In addition, the present embodiment discloses a data processing method, which specifically includes, but is not limited to, including steps S241 to S246.
Step S241, two linearly related target solution space data are obtained;
in step S241, two of the plurality of target solution space data are acquired, which are linearly related.
It should be noted that the linear correlation is: for example: if a.X + b.Y is equal to 0, X and Y are linearly related, where X and Y represent two target solution space data.
For example: NullSpace (A)20 all) And NullSpace (A)21 all)。
Step S242, splicing the two target solution space data in the column direction to obtain corresponding spliced solution space data;
in step S242, the last line position of one target solution space data is spliced with the first line position of another target solution space data to obtain corresponding spliced solution space data.
Step S243, transposing the splicing solution spatial data to obtain transposed solution spatial data;
by performing steps S242 to S243, for example: target solution space data NullSpace (A)20 all)：
NullSpace (A)20 all) And NullSpace (A)21 all) Splicing and transposing to obtain:
it should be noted that it is necessary to analyze that neither the last 12 columns nor the first 40 columns are zero respectively to indicate that there is linear correlation between the two spaces, otherwise it is meaningless to solve the space as zero.
Step S244, intercepting and transposing the preset column of the transposed spatial data to obtain intercepted spatial data;
in step S244, the transposed spatial data is captured according to the predetermined column data, and then the captured transposed spatial data is transposed to obtain the captured spatial data.
It should be noted that, corresponding preset line data is preset according to the number of lines of the two spliced target solution space data, and the number of lines of the target solution space data is consistent with the preset line data.
For example: target solution space data NullSpace (A)20 all) Has 40 columns (first 40 columns) of solution base data, and NullSpace (A) of target solution space data21 all) Has 12 columns (last 12 columns), target solution space data NullSpace (A)20 all) And target solution space data NullSpace (A)21 all) The spliced solution space data has 52 columns of solution base data, the preset columns of data of the first 40 columns or the last 12 columns of the transposed solution space data are intercepted, and the transposition processing is carried out. Wherein, if the current 40 columns and the last 12 columns are not zero at the same time, it can be indicated that the two solution space sets have non-zero solutions, and the intersection of the two target solution space data can be obtained.
Transposing the solution space data into the first 40 columns of intercepted data, and then acquiring the target solution space data corresponding to the first 40 columns of intercepted data, namely NullSpace (A)20 all) And transpose the solution space data and the target solution space data NullSpace (a)20 all) Multiplication processing is performed.
Step S245, multiplying the target solution space data and the intercepted solution space data and solving by taking the sum as zero to obtain intersection solution space data;
in step S245, the target solution space data and the truncated solution space data are subjected to multiplication algorithm processing, and the sum of the multiplication results is zero to be solved, so as to obtain the intersection solution space data.
It should be noted that the intersection solution space data includes a plurality of solution base data, and when the solution base data is all 0, the solution base data of all 0 is removed.
For example: target solution space data NullSpace (A)20 all) And target solution space data NullSpace (A)20 all) Multiplying the corresponding intercepted solution space data, and solving by taking the sum as zero to obtain:
{{0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1},{0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1,0,0,0},{0,0,0,0,0,0,0,0,0,0,2,-1,0,0,0,0,0,0},{0,0,0,0,0,0,0,2,-1,0,0,0,0,0,0,0,0,0},{0,0,0,0,2,-1,0,0,0,0,0,0,0,0,0,0,0,0},{0,2,-1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0}}
and removing all 0 solution base data to obtain:
{{0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1},{0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1,0,0,0},{0,0,0,0,0,0,0,2,-1,0,0,0,0,0,0,0,0,0},{0,0,0,0,2,-1,0,0,0,0,0,0,0,0,0,0,0,0}}
by performing steps S241 to S245, first, two linearly related target solution space data of the plurality of target solution space data are acquired. And then, splicing the position of the last line of one target solution space data with the position of the first line of the other target solution space data to obtain corresponding spliced solution space data. And secondly, transposing the splicing solution space data to obtain transposed solution space data. Then, the transposition solution space data are intercepted according to the preset column data, and then the intercepted transposition solution space data are transposed to obtain the interception solution space data. And finally, multiplying the target solution space data and the intercepted solution space data by using a multiplication algorithm, and solving the result obtained by multiplying by taking the sum as zero to obtain the intersection solution space data.
It should be noted that, by repeatedly executing steps S241 to S245, intersection solution space data of any two target solution space numbers having linear correlations is obtained.
Referring to fig. 8, a flowchart of a data processing method in an embodiment of the present invention is shown. In addition, the present embodiment discloses a data processing method, which specifically includes, but is not limited to, including step S251 to step S252.
Step S251, acquiring combined solution space data according to the intersection solution space data;
in step S251, the number and the numerical range of the solution base data of each intersection solution space data are acquired, and the combined solution space data of the corresponding number is acquired according to the number and the numerical range.
It should be noted that the number of the acquired combined solution space data is the same as the number of the solution base data of the intersection solution space data.
For example: target solution space data NullSpace (A)20 all) And target solution space data NullSpace (A)20 all) Multiplying the corresponding intercepted solution space data and solving by taking the sum as zero to obtain:
{{0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,-1,0,0,0,0,0,0,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1,0,0,0},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,-1},{0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1},{0,0,0,0,0,0,0,0,0,0,0,0,0,2,-1,0,0,0},{0,0,0,0,0,0,0,2,-1,0,0,0,0,0,0,0,0,0},{0,0,0,0,2,-1,0,0,0,0,0,0,0,0,0,0,0,0}}
the number of the solution base data is 8, and the numerical range of the solution base data is obtained: { -2, -1,0,1,2} and { -2, -1,1,2 }.
Obtaining combined solution space data according to the number of the solution base data and the numerical range of the solution base data:
Xssarray
＝{{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,0,1,2},{-2,-1,0,1,2}}
step S252, performing solution processing on the combined solution space data according to a preset solution algorithm to obtain communication evaluation data.
In step S252, the combined solution space data is substituted into a preset solution algorithm to be solved, so as to obtain communication evaluation data.
For example: the combined solution space data is:
Xssarray
＝{{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,1,2},{-2,-1,0,1,2},{-2,-1,0,1,2}}
solving to obtain communication evaluation data:
{0,0,0,0,4,0,0,-4,4,0,0,0,0,-4,4,0,-4,0}、{0,0,0,0,-4,4,0,4,0,0,0,0,0,-4,4,0,-4,0}
{0,0,0,0,2,1,0,-2,3,0,0,0,0,-2,3,0,-2,-1}、{0,0,0,0,-2,3,0,2,1,0,0,0,0,-2,3,0,-2,-1}
{0,0,0,0,2,1,0,-2,3,0,0,0,0,2,1,0,2,-3}、{0,0,0,0,-2,3,0,2,1,0,0,0,0,2,1,0,2,-3}
{0,0,0,0,4,0,0,-4,4,0,0,0,0,4,0,0,4,-4}、{0,0,0,0,-4,4,0,4,0,0,0,0,0,4,0,0,4,-4}
{0,0,0,0,4,0,0,-4,4,0,0,0,0,-4,0,0,-4,4}、{0,0,0,0,-4,4,0,4,0,0,0,0,0,-4,0,0,-4,4}
{0,0,0,0,2,1,0,-2,3,0,0,0,0,-2,-1,0,-2,3}、{0,0,0,0,-2,3,0,2,1,0,0,0,0,-2,-1,0,-2,3}
{0,0,0,0,2,1,0,-2,3,0,0,0,0,2,-3,0,2,1}、{0,0,0,0,-2,3,0,2,1,0,0,0,0,2,-3,0,2,1}
{0,0,0,0,4,0,0,-4,4,0,0,0,0,4,-4,0,4,0}、{0,0,0,0,-4,4,0,4,0,0,0,0,0,4,-4,0,4,0}
{0,0,0,0,-2,3,0,4,-1,0,0,0,0,-2,3,0,-4,1}、{0,0,0,0,4,0,0,-2,2,0,0,0,0,-4,4,0,-2,0}
{0,0,0,0,-4,4,0,2,0,0,0,0,0,4,0,0,2,-2}、{0,0,0,0,2,1,0,-4,3,0,0,0,0,2,1,0,4,-3}
through executing the steps S251 to S252, the number and the numerical range of the solution base data of each intersection solution space data are obtained, the corresponding number of combined solution space data are obtained according to the number and the numerical range, and the combined solution space data are substituted into the preset solution algorithm to be solved, so that the communication evaluation data are obtained, and the complexity of the operation is greatly reduced.
In addition, referring to fig. 9, one embodiment of the present invention discloses a data processing apparatus. The data processing apparatus includes: the system comprises an acquisition module 100, an analysis module 200, an acquisition unit 210, a conversion unit 220, a summary unit 230, an intersection unit 240 and a solving unit 250. Wherein, the analysis module 200 comprises: the system comprises an acquisition unit 210, a conversion unit 220, a summary unit 230, an intersection unit 240 and a solving unit 250. The acquisition module 100, the analysis module 200, the acquisition unit 210, the conversion unit 220, the summarization unit 230, the intersection unit 240 and the solving unit 250 are all connected in communication.
The acquisition module 100 acquires communication transmission data. The analysis module 200 performs data analysis on the communication transmission data to obtain communication evaluation data. The acquisition unit 210 acquires sequence data of communication transmission data. The conversion unit 220 performs linear operation conversion processing on the sequence data to obtain initial solution space data. The summarizing unit 230 summarizes the initial solution space data to obtain the target solution space data. The intersection unit 240 obtains data of an intersection in the target solution space data to obtain intersection solution space data. The solving unit 250 performs solution processing on the intersection solution space data according to a preset solving algorithm to obtain communication evaluation data.
The obtaining module 100 obtains transmission data after spatial matrix communication coding to obtain communication transmission data, and the analyzing module 200 performs solution analysis on correlation coefficient data of the communication transmission data to obtain communication evaluation data. The analysis module 200 performs solution analysis on the correlation coefficient data of the communication transmission data, including: first, the acquisition unit 210 acquires an autocorrelation equation of communication transmission data to obtain sequence data. Then, the conversion unit 220 performs linearization processing on the sequence data according to the quadratic coefficient of each sequence data, and reduces the dimension of the sequence data to a linear equation system to obtain initial solution space data. Next, the summarizing unit 230 finds more solution space data of each sequence data, and summarizes the solution space data and the initial solution space data to obtain target solution space data. Then, the intersection unit 240 obtains data where all the target solution space data have an intersection, so as to obtain intersection solution space data. Finally, the solving unit 250 performs solution processing on the intersection solution space data according to a preset solving algorithm, and solves an intersection solution space numerical value solution to obtain communication evaluation data.
The operation process of the data processing apparatus of this embodiment specifically refers to steps S100 to S200 and steps S210 to S250 of the data processing method in fig. 1 and fig. 2 described above, and is not described again here.
Another embodiment of the present invention discloses a data processing apparatus including: at least one processor, and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform any one of the data processing methods of method steps S100 to S200 in fig. 1, method steps S210 to S250 in fig. 2, method steps S221 to S224 in fig. 3, method steps S2211 and S2212 in fig. 4, method steps S221 to S233 in fig. 5, method steps S234 to S236 in fig. 6, method steps S241 to S245 in fig. 7, and method steps S251 and S252 in fig. 8.
Another embodiment of the present invention discloses a computer-readable storage medium, including: the computer-readable storage medium stores computer-executable instructions for causing a computer to execute any one of the data processing methods of method steps S100 to S200 in fig. 1, method steps S210 to S250 in fig. 2, method steps S221 to S224 in fig. 3, method steps S2211 and S2212 in fig. 4, method steps S221 to S233 in fig. 5, method steps S234 to S236 in fig. 6, method steps S241 to S245 in fig. 7, and method steps S251 and S252 in fig. 8.
The above-described embodiments of the apparatus are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as is well known to those skilled in the art.
The embodiments of the present invention have been described in detail with reference to the accompanying drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present invention. Furthermore, the embodiments of the present invention and the features of the embodiments may be combined with each other without conflict.
Claims (10)
1. A data processing method, comprising:
acquiring communication transmission data;
performing data analysis on the communication transmission data to obtain communication evaluation data;
the performing data analysis on the communication transmission data to obtain communication evaluation data includes:
acquiring sequence data of the communication transmission data;
performing linear operation conversion processing on the sequence data to obtain initial solution space data;
summarizing the initial solution space data to obtain target solution space data;
acquiring intersection data in the target solution space data to obtain intersection solution space data;
and performing solution processing on the intersection solution space data according to a preset solution algorithm to obtain the communication evaluation data.
2. The data processing method of claim 1, wherein performing linear operation transformation processing on the sequence data to obtain initial solution space data comprises:
acquiring coefficient matrix data corresponding to the sequence data;
performing solving processing by taking the sum of the coefficient matrix data as zero to obtain first solution space data, wherein the first solution space data comprises a plurality of solution base data;
adding any two pieces of base data between the plurality of pieces of first solution space data, and/or multiplying the base data by a preset scalar to obtain second solution space data;
determining the initial solution space data according to the first solution space data and the second solution space data.
3. The data processing method according to claim 2, wherein the obtaining coefficient matrix data corresponding to the sequence data comprises:
expressing the sequence data by a preset linear equation expression to obtain a target linear equation, wherein the preset linear equation expression is formed by combining preset parameters, a coefficient matrix and transposed data of the preset parameters;
and acquiring the coefficient matrix in the target linear equation to obtain the coefficient matrix data.
4. The data processing method according to claim 1, wherein the summarizing the initial solution space data to obtain target solution space data comprises:
acquiring coefficient matrix data corresponding to the sequence data;
transposing the coefficient matrix data to obtain transposed matrix data;
solving processing is carried out by taking the sum of the transposed matrix data as zero to obtain third solution space data;
and summarizing the third solution space data and the initial solution space data to obtain the target solution space data.
5. The data processing method according to claim 4, wherein the aggregating the initial solution space data to obtain target solution space data further comprises:
performing corresponding processing on the coefficient matrix data according to a preset processing rule to obtain conversion matrix data;
solving is carried out by taking the sum of the conversion matrix data as zero to obtain fourth solution space data;
and summarizing the third solution space data, the fourth solution space data and the initial solution space data to obtain the target solution space data.
6. The data processing method according to any one of claims 1 to 5, wherein the obtaining data of the intersection in the target solution space data to obtain intersection solution space data includes:
acquiring two linearly related target solution space data;
performing column direction splicing processing on the two target solution space data to obtain corresponding spliced solution space data;
transposing the splicing solution spatial data to obtain transposed solution spatial data;
intercepting and transposing the preset column of the transposed solution spatial data to obtain intercepted solution spatial data;
and multiplying the target solution space data and the intercepted solution space data and solving by taking the sum as zero so as to obtain the intersection solution space data.
7. The data processing method according to any one of claims 1 to 5, wherein the performing solution processing on the intersection solution space data according to a preset solution algorithm to obtain the communication evaluation data comprises:
acquiring combined solution space data according to the intersection solution space data;
and solving the combined solution space data according to the preset solving algorithm to obtain the communication evaluation data.
8. A data processing apparatus, characterized by comprising:
the acquisition module is used for acquiring communication transmission data;
the analysis module is used for carrying out data analysis on the communication transmission data to obtain communication evaluation data;
the analysis module comprises:
an acquisition unit configured to acquire sequence data of the communication transmission data;
the conversion unit is used for carrying out linear operation conversion processing on the sequence data to obtain initial solution space data;
the summarizing unit is used for summarizing the initial solution space data to obtain target solution space data;
the intersection unit is used for acquiring intersection data in the target solution space data to obtain intersection solution space data;
and the solving unit is used for solving the intersection solution space data according to a preset solving algorithm so as to obtain the communication evaluation data.
9. A data processing apparatus, characterized by comprising:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the data processing method of any one of claims 1 to 7.
10. A computer-readable storage medium storing computer-executable instructions for causing a computer to perform the data processing method of any one of claims 1 to 7.
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