CN113792185A - Method, apparatus, computer device and storage medium for estimating missing signal - Google Patents
Method, apparatus, computer device and storage medium for estimating missing signal Download PDFInfo
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Abstract
The present application relates to a method, apparatus, computer device and storage medium for estimating a missing signal. The method comprises the following steps: receiving a signal sequence to be estimated sent by a sending end, wherein the signal sequence to be estimated has signal data loss, and the signal data which is not lost in the signal sequence to be estimated is represented as a known signal data group; acquiring each signal data group to be estimated, wherein the signal data group to be estimated is estimation experiment data of lost signal data in a signal sequence to be estimated; calculating the distance between each signal data group to be estimated and the known signal data group according to a pre-constructed objective function and the known signal data group, and determining the signal data group to be estimated with the minimum distance from the known signal data group as an estimated signal data group; the estimation signal data group is estimation result data of signal data lost in the signal sequence to be estimated, and the objective function represents the minimum distance between the signal data group to be estimated and the known signal data group. By adopting the method, the signal estimation accuracy can be improved.
Description
Technical Field
The present application relates to the field of data communication technologies, and in particular, to a method and an apparatus for estimating a missing signal, a computer device, and a storage medium.
Background
With the development of data communication technology, in order to reduce the influence caused by signal loss and noise interference occurring in the communication process, a missing signal estimation technology has appeared, which aims to make the communication data/signal obtained by the receiving side as close as possible to the communication data/signal sent by the sending side.
In the conventional technology, an average value of known data is generally used for filling missing data by using a mean filling method, or data with the largest occurrence number in the known data is used for filling missing data by using a mode filling method.
However, the conventional method, whether average filling or mode filling, considers the dimension of the information to be relatively single when determining the value to be filled, and thus results in low accuracy of signal estimation.
Disclosure of Invention
In view of the above, it is necessary to provide a method, an apparatus, a computer device and a storage medium for estimating a missing signal, which can improve the accuracy of signal estimation.
A method for estimating a missing signal is applied to a receiving end, and comprises the following steps:
receiving a signal sequence to be estimated sent by a sending end, wherein the signal sequence to be estimated has signal data loss, and the signal data which is not lost in the signal sequence to be estimated is represented as a known signal data group;
acquiring each signal data group to be estimated, wherein the signal data group to be estimated is estimation experiment data of lost signal data in the signal sequence to be estimated;
calculating the distance between each signal data group to be estimated and a known signal data group according to a pre-constructed objective function, and determining the signal data group to be estimated with the minimum distance from the known signal data group as an estimated signal data group;
wherein the estimation signal data group is estimation result data of signal data lost in the signal sequence to be estimated, and the objective function represents a minimum distance between the signal data group to be estimated and the known signal data group.
In one embodiment, the known signal data set includes known signal data, and the signal data set to be estimated includes signal data to be estimated, the method further includes:
acquiring each piece of known signal data, a first position of each piece of known signal data in the signal sequence to be estimated and a second position of each piece of signal data to be estimated in the signal sequence to be estimated from the signal sequence to be estimated;
setting each piece of signal data to be estimated as a first value, and constructing a known signal data group according to each piece of known signal data, the first position and the second position, wherein the position of each piece of known signal data in the known signal data group is the same as the position of each piece of known signal data in the signal sequence to be estimated; and the length of the known signal data group is the same as that of the signal sequence to be estimated.
In one embodiment, the method further comprises:
setting each known signal data in the known signal data group as a second value, and constructing to-be-estimated signal data groups by using each to-be-estimated signal data as a variable;
wherein the second value and the first value are equal.
In one embodiment, determining the signal data group to be estimated with the smallest distance from the known signal data group as the estimated signal data group includes:
when the target function obtains the minimum distance, solving the partial derivative of the target function to obtain the partial derivative of the target function;
and setting the partial derivative of the target function to zero, calculating to obtain a signal data group to be estimated with the minimum distance from the known signal data group, and determining the signal data group to be estimated as an estimated signal data group.
In one embodiment, the signal sequence to be estimated includes the known signal data set and the signal data set to be estimated, and the method further includes:
calculating a second-order difference of the signal sequence to be estimated according to a second-order difference matrix and the signal sequence to be estimated;
obtaining the distance between the signal data group to be estimated and the known signal data group according to the second-order difference, wherein the distance is used for representing the similarity between the signal data group to be estimated and the known signal data group;
and obtaining the minimum value of the distance to obtain the constructed target function.
In one embodiment, obtaining the distance between the signal data group to be estimated and the known signal data group according to the second-order difference includes:
multiplying the second-order difference matrix by the known signal data group and the signal data group to be estimated respectively to obtain a first product and a second product respectively;
and adding the first product and the second product, and squaring the sum of the first product and the second product to obtain the distance between the signal data group to be estimated and the known signal data group.
An apparatus for estimating a missing signal, the apparatus comprising:
the device comprises a signal sequence to be estimated acquisition module, a signal data acquisition module and a signal data acquisition module, wherein the signal sequence to be estimated acquisition module is used for receiving a signal sequence to be estimated sent by a sending end, the signal data of the signal sequence to be estimated is lost, and the signal data which is not lost in the signal sequence to be estimated is represented as a known signal data group;
a to-be-estimated signal data group acquisition module, configured to acquire each to-be-estimated signal data group, where the to-be-estimated signal data group is estimation experiment data of signal data lost in the to-be-estimated signal sequence;
the estimation signal data group acquisition module is used for calculating the distance between each signal data group to be estimated and the known signal data group according to a pre-constructed objective function and determining the signal data group to be estimated with the minimum distance to the known signal data group as an estimation signal data group; wherein the estimation signal data group is estimation result data of signal data lost in the signal sequence to be estimated, and the objective function represents a minimum distance between the signal data group to be estimated and the known signal data group.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
receiving a signal sequence to be estimated sent by a sending end, wherein the signal sequence to be estimated has signal data loss, and the signal data which is not lost in the signal sequence to be estimated is represented as a known signal data group;
acquiring each signal data group to be estimated, wherein the signal data group to be estimated is estimation experiment data of lost signal data in the signal sequence to be estimated;
calculating the distance between each signal data group to be estimated and a known signal data group according to a pre-constructed objective function, and determining the signal data group to be estimated with the minimum distance from the known signal data group as an estimated signal data group;
wherein the estimation signal data group is estimation result data of signal data lost in the signal sequence to be estimated, and the objective function represents a minimum distance between the signal data group to be estimated and the known signal data group.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
receiving a signal sequence to be estimated sent by a sending end, wherein the signal sequence to be estimated has signal data loss, and the signal data which is not lost in the signal sequence to be estimated is represented as a known signal data group;
acquiring each signal data group to be estimated, wherein the signal data group to be estimated is estimation experiment data of lost signal data in the signal sequence to be estimated;
calculating the distance between each signal data group to be estimated and a known signal data group according to a pre-constructed objective function, and determining the signal data group to be estimated with the minimum distance from the known signal data group as an estimated signal data group;
wherein the estimation signal data group is estimation result data of signal data lost in the signal sequence to be estimated, and the objective function represents a minimum distance between the signal data group to be estimated and the known signal data group.
The method, the device, the computer equipment and the storage medium for estimating the missing signal receive the signal sequence to be estimated sent by the sending end, and the signal data loss exists in the signal sequence to be estimated. And acquiring each signal data group to be estimated, calculating the distance between each signal data group to be estimated and the known signal data group according to a pre-constructed objective function and the known signal data group, and determining the signal data group to be estimated with the minimum distance from the known signal data group as an estimated signal data group. When the signal data to be estimated is estimated, the distribution information of the signal data to be estimated and the known signal data is considered, so that the signal estimation accuracy can be improved.
Drawings
FIG. 1 is a diagram of an exemplary embodiment of a method for estimating a missing signal;
FIG. 2 is a flow diagram illustrating a method for estimating a missing signal according to one embodiment;
FIG. 3 is a comparison of pre and post states for estimating a missing signal in one embodiment;
FIG. 4 is a block diagram of an apparatus for estimating a missing signal in one embodiment;
FIG. 5 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is 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 present application and are not intended to limit the present application.
The method for estimating the missing signal provided by the application can be applied to the application environment shown in fig. 1. The method comprises a sending end 102 and a receiving end 104, wherein the sending end 102 sends a signal sequence, and the receiving end 104 receives the signal sequence sent by the sending end 102. The signal sequence transmitted by the transmitting end 102 may have signal loss, so that the receiving end 104 receives the signal sequence with signal data loss, which is called a signal sequence to be estimated. After receiving the signal sequence to be estimated, the receiving terminal acquires each signal data group to be estimated, calculates the distance between each signal data to be estimated and the known signal data group according to a pre-constructed objective function, and determines the signal data group to be estimated with the minimum distance from the known signal data group as an estimated signal data group, wherein the estimated signal data group is estimation result data of missing signal data in the signal sequence to be estimated. The sending end 102 and the receiving end 104 may be, but are not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices.
In one embodiment, as shown in fig. 2, a method for estimating a missing signal is provided, which is described by taking the method as an example applied to the terminal in fig. 1, and includes the following steps:
step 202, receiving a signal sequence to be estimated sent by a sending end, where the signal sequence to be estimated has signal data loss, and the signal data that is not lost in the signal sequence to be estimated is represented as a known signal data group.
In the process of sending signal data by a sending end, the signal data form an ordered sequence according to a generation sequence, and the ordered sequence is called a signal sequence. In the transmission process of signal data, signal data is lost due to factors such as distance or transmission line, a signal sequence with signal data loss is called a signal sequence to be estimated, and the signal sequence to be estimated comprises a known signal data group and lost signal data. The signal sequence to be estimated is related to time, and two signal sequences to be estimated with completely the same signal data content still do not belong to the same signal sequence to be estimated due to different time information carried by the two signal sequences. The signal sequence to be estimated has corresponding positions of all signal data, and even if signal data loss exists in a certain position, the position where the signal data loss exists can be determined.
When the loss of the signal data occurs, for a segment of signal sequence to be estimated sent by a sending end, when the segment of signal sequence to be estimated does not completely lose the signal data, namely when there is no signal data to be lost, the signal data not to be lost in the signal sequence to be estimated is represented as a known signal data group. A segment of signal sequence to be estimated usually includes not only a known signal data set but also lost signal data, so in order to obtain a signal sequence to be estimated that is sent by a sending end as close as possible, a receiving end needs to estimate the lost signal data (estimate a lost signal) to obtain a complete estimated signal sequence, where the estimated signal sequence includes the known signal data set and the estimated signal data set.
And 204, acquiring each signal data group to be estimated, wherein the signal data group to be estimated comprises each signal data to be estimated.
Each signal data group to be estimated is estimation experimental data acquired by the receiving end for estimating a missing signal, and is used for representing the missing signal data in the signal sequence to be estimated. The receiving end can obtain various signal data sets to be estimated in various ways, and optionally, the signal data sets to be estimated are obtained through a neural network model. Unlike the signal data set to be estimated in the above step, the signal data set to be estimated here is a plurality of sets of estimation test data, and the signal data set to be estimated in the above step is equivalent to an unknown number and is a variable.
And step 206, calculating the distance between each signal data group to be estimated and the known signal data group according to a pre-constructed objective function and the known signal data group, and determining the signal data group to be estimated with the minimum distance from the known signal data group as an estimated signal data group.
Wherein the estimation signal data group is estimation result data of signal data lost in the signal sequence to be estimated, and the objective function represents a minimum distance between the signal data group to be estimated and the known signal data group.
Specifically, the estimation signal data group is estimation data of signal data lost in the signal sequence to be estimated, which is to be finally acquired by the receiving end. For a segment of the signal sequence to be estimated, the known signal data set is determined. After each signal data group to be estimated is obtained, each signal data group to be estimated is substituted into an objective function, and the distance between each signal data group to be estimated and a known signal data group is calculated according to the objective function and the known signal data group which are constructed in advance. And when the distance between one of the signal data groups to be estimated and the known signal data group is minimum relative to the distance between the other signal data groups to be estimated and the known signal data group, determining the signal data group to be estimated with the minimum distance to the known signal data group as an estimated signal data group. As shown in fig. 3(a), the signal data of the signal sequence to be estimated is absent before the signal sequence to be estimated is estimated. Fig. 3(b) is a diagram showing an estimated signal sequence obtained by estimating a signal sequence to be estimated. The signal sequence sent by the sending end is close to the graph (b) in fig. 3, so the estimation signal sequence obtained by the method for the signal sequence to be estimated is smooth and has higher accuracy.
In the method for estimating the missing signal, a signal sequence to be estimated sent by a sending end is received, and signal data loss exists in the signal sequence to be estimated. And acquiring each signal data group to be estimated, calculating the distance between each signal data group to be estimated and the known signal data group according to a pre-constructed objective function and the known signal data group, and determining the signal data group to be estimated with the minimum distance from the known signal data group as an estimated signal data group. When the signal data to be estimated is estimated, the distribution information of the signal data to be estimated and the known signal data is considered, so that the signal estimation accuracy can be improved.
In one embodiment, the known signal data set includes known signal data, and the signal data set to be estimated includes signal data to be estimated, the method further includes: acquiring each piece of known signal data, a first position of each piece of known signal data in the signal sequence to be estimated and a second position of each piece of signal data to be estimated in the signal sequence to be estimated from the signal sequence to be estimated; setting each piece of signal data to be estimated as a first value, and constructing a known signal data group according to each piece of known signal data, the first position and the second position, wherein the position of each piece of known signal data in the known signal data group is the same as the position of each piece of known signal data in the signal sequence to be estimated; and the length of the known signal data group is the same as that of the signal sequence to be estimated.
The position of the known signal data in the signal sequence is referred to as a first position, and the position of the signal data to be estimated in the signal sequence to be estimated is referred to as a second position. Before the missing signal estimation is carried out on the signal sequence to be estimated, the method also comprises a preprocessing process. In one embodiment, signal data to be estimated in a signal sequence to be estimated are uniformly identified, an N-order identity matrix is generated, and the number of the signal data to be estimated is counted; determining the quantity of known signal data according to a signal sequence to be estimated; and calculating to obtain a first position index of the known signal data and a second position index of the signal data to be estimated according to the number of the signal data to be estimated and the number of the known signal data. And extracting corresponding row vectors from the unit matrix according to the first position index to form a screening matrix. The screening matrix is a K × N matrix for screening the known signal data from the signal sequence to be estimated.
And generating a screening matrix and then combining the signal sequence to be estimated to obtain a known signal data set, wherein the known signal data set comprises known signal data, the known signal data set comprises each known signal data and a first position of each known signal data in the signal sequence to be estimated. The length data of the known signal data set is the same as the number data of the known signal data. For example, when there are 5 pieces of known signal data and 3 pieces of signal data to be estimated in the signal sequence to be estimated, the length data of the known signal data set is 5.
For example, when the filtering matrix is N-5, K-3, and the 1 st, 2 nd and 5 th of the signal sequence x to be estimated are known signal data, then the filtering matrix is a new matrix formed by extracting the 1 st, 2 nd and 5 th rows from the 5 th order identity matrix, that is:
wherein, the signal sequence to be estimated may be represented as x ═ x0，x1，…，xn-1]And combining the signal sequence to be estimated according to the screening matrix to obtain a known signal data set y:
and acquiring a second position corresponding to each signal data to be estimated in the signal sequence to be estimated while acquiring the known signal data set. The set of known signal data is then converted into a set of known signal data. Specifically, each signal data to be estimated is set to a first value, and a known signal data set is constructed according to each known signal data, the first position and the second position. Unlike the known signal data set, the length of the known signal data group is the same as the length of the signal sequence to be estimated, and the known signal data group is added with the signal data portion to be estimated except that the positions of the known signal data and the known signal data in the signal sequence to be estimated are kept unchanged. Accordingly, the signal data to be estimated is distributed in the known signal data set by its second position in the signal sequence to be estimated. After obtaining the form with the same length as the signal sequence to be estimated, for the convenience of subsequent calculation, it may be selected to retain only the known signal data therein or to facilitate subsequent cancellation, and the signal data to be estimated at each second position is set to the first value. Optionally, the first value is set to 0, the known signal data group only includes known signal data, and the signal data to be estimated are all 0.
In this embodiment, a known signal data set is obtained by acquiring known signal data and a first position corresponding to the known signal data and a second position corresponding to signal data to be estimated, and setting the signal data to be estimated as a first value, so that the signal data to be estimated in the obtained known signal data set are kept uniform and are the first value, thereby facilitating subsequent calculation.
In one embodiment, the method of estimating a missing signal further comprises: setting each known signal data in the known signal data group as a second value, and constructing to-be-estimated signal data groups by using each to-be-estimated signal data as a variable; and the sum of the second value and the first value is a preset value, and the signal data group to be estimated comprises each signal data to be estimated and a corresponding second position of the signal data in the signal sequence to be estimated.
Specifically, a complementary matrix of the screening matrix is obtained by calculation according to the screening matrix, and taking the screening matrix as an example, the complementary matrix is expressed as:
the complement matrix functions to set each known signal data in the set of known signal data to a second value. The second value is equal to the first value, and optionally, when the preset value is 0, both the first value and the second value may be 0. And after setting each known signal data in the known signal data group as a second value, constructing and obtaining a signal data group to be estimated according to each signal data to be estimated as a variable.
After the known signal data group and the signal data group to be estimated are obtained, the known signal data group and the signal data group to be estimated are added to obtain a signal sequence to be estimated, and the estimated signal data group is obtained when the estimated signal data group is obtained through calculation according to the target function and the known signal data group. For example, v is a signal data group to be estimated, and the signal sequence to be estimated can be expressed as:
in this embodiment, a signal data group to be estimated can be constructed by setting each known signal data in the known signal data group to a second value and using each signal data to be estimated as a variable. The known signal data in the obtained signal data group to be estimated are kept uniform and are all the second values, so that the subsequent calculation is facilitated.
In one embodiment, when the objective function obtains the minimum distance, the partial derivative of the objective function is obtained by solving the partial derivative of the objective function; and setting the partial derivative of the target function to zero, calculating to obtain a signal data group to be estimated with the minimum distance from the known signal data group, and determining the signal data group to be estimated as an estimated signal data group.
When the target function obtains the minimum distance, the signal data group to be estimated with the minimum distance to the known signal data group is found according to the target function. And solving the partial derivative of the target function to obtain the partial derivative, wherein the partial derivative is a formula, and the formula comprises a signal data group to be estimated and a known signal data group which are used as variables. And setting the partial derivative to be zero to obtain a minimum value of the objective function, so that the signal data group to be estimated, which is used as a variable, can be solved to obtain a signal data group to be estimated, which has the minimum distance from the known signal data group, and the signal data group to be estimated is used as an estimated signal data group.
In this embodiment, the target function is subjected to partial derivation, the partial derivation is set to zero, a signal data group to be estimated, which is the smallest distance from a known signal data group, is obtained through calculation, and the signal data group to be estimated is used as an estimated signal data group.
In one embodiment, the signal sequence to be estimated includes the known signal data set and a signal data set to be estimated, the method further includes: acquiring the known signal data group and the signal data group to be estimated to obtain the signal sequence to be estimated; calculating a second-order difference of the signal sequence to be estimated according to a second-order difference matrix and the signal sequence to be estimated; obtaining the distance between the signal data group to be estimated and the known signal data group according to the second-order difference, wherein the distance is used for representing the similarity between the signal data group to be estimated and the known signal data group; and obtaining the minimum value of the distance to obtain the constructed target function.
Specifically, in one embodiment, optionally, the objective function is constructed by using the second order difference as follows:
wherein D is a second order difference matrix, which is a known matrix, and specifically is:
substitution of D into
The following can be obtained:
for the norm of L2,
to pair
Taking the partial derivative for v and letting the partial derivative be 0, we can:
based on the formula, the method can further obtain
The estimated signal data set can be calculated according to the formula.
In this embodiment, the distance between the signal data group to be estimated and the known signal data group is obtained through the second order difference matrix and the norm formula, and the minimum value of the distance is taken, so that the constructed target function can be obtained.
In one embodiment, obtaining the distance between the signal data group to be estimated and the known signal data group according to the second-order difference includes: multiplying the second-order difference matrix by the known signal data group and the signal data group to be estimated respectively to obtain a first product and a second product respectively; and adding the first product and the second product, and squaring the sum of the first product and the second product to obtain the distance between the signal data group to be estimated and the known signal data group.
Specifically, the objective function formula expands as:
wherein STy is a known signal data set, Sc Tv is the signal data set to be estimated, DSTy is the first product, DSc Tv is the second product.
In this embodiment, the distance between the signal data set to be estimated and the known signal data set is amplified by selecting the norm formula of L2, so that the distance contrast between each signal data set to be estimated and the known signal data set is more obvious.
In one embodiment, a method of estimating a missing signal, comprises: receiving a signal sequence to be estimated sent by a sending end, wherein the signal sequence to be estimated has signal data loss, and the signal data which is not lost in the signal sequence to be estimated is represented as a known signal data group; the lost signal data in the signal sequence to be estimated is represented as a signal data group to be estimated;
according to a pre-constructed relation function, calculating to obtain a signal data group to be estimated with the minimum distance from the known signal data group, and determining the signal data group to be estimated as an estimated signal data group;
obtaining an estimated signal sequence according to the known signal data group and the estimated signal data group;
and the estimation signal data group is estimation result data of lost signal data in the signal sequence to be estimated.
Specifically, the relationship function is
The relation function is calculated according to the objective function. Specifically, calculating a partial derivative of the target function, setting the partial derivative of the target function to zero, and obtaining a minimum value of the target function, wherein the minimum value represents that a signal data group to be estimated, which is the minimum distance from a known signal data group, is obtained; from the minimum of the objective function, a relationship function can be obtained.
In this embodiment, an estimated signal data set having the smallest distance from the known signal data set can be obtained directly according to the known signal data set through the relationship function.
It should be understood that, although the steps in the flowcharts related to the above embodiments are shown in sequence as indicated by the arrows, the steps are not necessarily executed in sequence as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in each flowchart related to the above embodiments may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of performing the steps or stages is not necessarily sequential, but may be performed alternately or alternately with other steps or at least a part of the steps or stages in other steps.
In one embodiment, as shown in fig. 4, there is provided an apparatus for estimating a missing signal, including: a signal sequence to be estimated acquisition module 301, a signal data group to be estimated acquisition module 302, and an estimated signal data group acquisition module 303, wherein:
a to-be-estimated signal sequence obtaining module 301, configured to receive a to-be-estimated signal sequence sent by a sending end, where the to-be-estimated signal sequence has signal data loss, and signal data that is not lost in the to-be-estimated signal sequence is represented as a known signal data group;
a to-be-estimated signal data group acquisition module 302, configured to acquire each to-be-estimated signal data group, where the to-be-estimated signal data group is estimation experiment data of signal data lost in the to-be-estimated signal sequence;
an estimated signal data group obtaining module 303, configured to calculate, according to a pre-constructed objective function and the known signal data group, a distance between each to-be-estimated signal data group and the known signal data group, and determine, as an estimated signal data group, a to-be-estimated signal data group having a minimum distance from the known signal data group; wherein the estimation signal data group is estimation result data of signal data lost in the signal sequence to be estimated, and the objective function represents a minimum distance between the signal data group to be estimated and the known signal data group.
In one embodiment, the apparatus for estimating a missing signal further comprises: the device comprises a known signal data acquisition module, a second position determination module and a known signal data group construction module, wherein:
the known signal data acquisition module is used for acquiring each known signal data from a signal sequence to be estimated and a corresponding first position of each known signal data in the signal sequence to be estimated;
a second position determining module, configured to determine, according to each of the first positions and the signal sequence to be estimated, a second position corresponding to each signal data to be estimated in the signal sequence to be estimated;
a known signal data group construction module, configured to set the signal data to be estimated corresponding to each second location to a first value, and construct a known signal data group according to each known signal data and the first location, where a location of each known signal data in the known signal data group is the same as a location of each known signal data in the signal sequence to be estimated; and the length of the known signal data group is the same as that of the signal sequence to be estimated.
In one embodiment, the apparatus for estimating a missing signal further comprises: a to-be-estimated signal data group construction module, configured to set each known signal data in the known signal data group to a second value, and construct to obtain the to-be-estimated signal data group by using each to-be-estimated signal data as a variable; wherein the second value and the first value are equal.
In one embodiment, the estimated signal data set obtaining module is further configured to, when the objective function obtains a minimum distance, calculate a partial derivative of the objective function to obtain a partial derivative of the objective function; and setting the partial derivative of the target function to zero, calculating to obtain a signal data group to be estimated with the minimum distance from the known signal data group, and determining the signal data group to be estimated as an estimated signal data group.
In one embodiment, the apparatus for estimating a missing signal further comprises: second order difference calculation module, distance acquisition module and distance minimum acquire the module, wherein:
the second-order difference calculation module is used for calculating the second-order difference of the signal sequence to be estimated according to a second-order difference matrix and the signal sequence to be estimated;
the distance acquisition module is used for acquiring the distance between the signal data group to be estimated and the known signal data group according to the second-order difference, wherein the distance is used for representing the similarity between the signal data group to be estimated and the known signal data group;
and the distance minimum value acquisition module is used for acquiring the minimum value of the distance to obtain the constructed target function.
For the specific limitation of the apparatus for estimating the missing signal, reference may be made to the above limitation of the method for estimating the missing signal, and details are not repeated here. The modules in the above apparatus for estimating a missing signal may be implemented in whole or in part by software, hardware, or a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 5. The computer device includes a processor, a memory, a communication interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a method of estimating a missing signal. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
Those skilled in the art will appreciate that the architecture shown in fig. 5 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database or other medium used in the embodiments provided herein can include at least one of non-volatile and volatile memory. Non-volatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical storage, or the like. Volatile Memory can include Random Access Memory (RAM) or external cache Memory. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method for estimating a missing signal, applied to a receiving end, the method comprising:
receiving a signal sequence to be estimated sent by a sending end, wherein the signal sequence to be estimated has signal data loss, and the signal data which is not lost in the signal sequence to be estimated is represented as a known signal data group;
acquiring each signal data group to be estimated, wherein the signal data group to be estimated is estimation experiment data of lost signal data in the signal sequence to be estimated;
calculating the distance between each signal data group to be estimated and a known signal data group according to a pre-constructed objective function, and determining the signal data group to be estimated with the minimum distance from the known signal data group as an estimated signal data group;
wherein the estimation signal data group is estimation result data of signal data lost in the signal sequence to be estimated, and the objective function represents a minimum distance between the signal data group to be estimated and the known signal data group.
2. The method of claim 1, wherein the set of known signal data includes each known signal data, wherein the set of signal data to be estimated includes each signal data to be estimated, and wherein the method further comprises:
acquiring each piece of known signal data, a first position of each piece of known signal data in the signal sequence to be estimated and a second position of each piece of signal data to be estimated in the signal sequence to be estimated from the signal sequence to be estimated;
setting each piece of signal data to be estimated as a first value, and constructing a known signal data group according to each piece of known signal data, the first position and the second position, wherein the position of each piece of known signal data in the known signal data group is the same as the position of each piece of known signal data in the signal sequence to be estimated; and the length of the known signal data group is the same as that of the signal sequence to be estimated.
3. The method of claim 2, further comprising:
setting each known signal data in the known signal data group as a second value, and constructing to-be-estimated signal data groups by using each to-be-estimated signal data as a variable;
wherein the second value and the first value are equal.
4. The method of claim 1, wherein determining a signal data set to be estimated having a minimum distance from the known signal data set as an estimated signal data set comprises:
when the target function obtains the minimum distance, solving the partial derivative of the target function to obtain the partial derivative of the target function;
and setting the partial derivative of the target function to zero, calculating to obtain a signal data group to be estimated with the minimum distance from the known signal data group, and determining the signal data group to be estimated as an estimated signal data group.
5. The method of claim 1, wherein the signal sequence to be estimated comprises the known signal data set and a signal data set to be estimated, the method further comprising:
calculating a second-order difference of the signal sequence to be estimated according to a second-order difference matrix and the signal sequence to be estimated;
obtaining the distance between the signal data group to be estimated and the known signal data group according to the second-order difference, wherein the distance is used for representing the similarity between the signal data group to be estimated and the known signal data group;
and obtaining the minimum value of the distance to obtain the constructed target function.
6. The method of claim 5, wherein obtaining the distance between the signal data set to be estimated and the known signal data set according to the second-order difference comprises:
multiplying the second-order difference matrix by the known signal data group and the signal data group to be estimated respectively to obtain a first product and a second product respectively;
and adding the first product and the second product, and squaring the sum of the first product and the second product to obtain the distance between the signal data group to be estimated and the known signal data group.
7. An apparatus for estimating a missing signal, the apparatus comprising:
the device comprises a signal sequence to be estimated acquisition module, a signal data acquisition module and a signal data acquisition module, wherein the signal sequence to be estimated acquisition module is used for receiving a signal sequence to be estimated sent by a sending end, the signal data of the signal sequence to be estimated is lost, and the signal data which is not lost in the signal sequence to be estimated is represented as a known signal data group;
a to-be-estimated signal data group acquisition module, configured to acquire each to-be-estimated signal data group, where the to-be-estimated signal data group is estimation experiment data of signal data lost in the to-be-estimated signal sequence;
the estimation signal data group acquisition module is used for calculating the distance between each signal data group to be estimated and the known signal data group according to a pre-constructed objective function and determining the signal data group to be estimated with the minimum distance to the known signal data group as an estimation signal data group; wherein the estimation signal data group is estimation result data of signal data lost in the signal sequence to be estimated, and the objective function represents a minimum distance between the signal data group to be estimated and the known signal data group.
8. The apparatus of claim 7, further comprising:
the known signal data acquisition module is used for acquiring each known signal data from a signal sequence to be estimated and a corresponding first position of each known signal data in the signal sequence to be estimated;
a second position determining module, configured to determine, according to each of the first positions and the signal sequence to be estimated, a second position corresponding to each signal data to be estimated in the signal sequence to be estimated;
a known signal data group construction module, configured to set the signal data to be estimated corresponding to each second location to a first value, and construct a known signal data group according to each known signal data and the first location, where a location of each known signal data in the known signal data group is the same as a location of each known signal data in the signal sequence to be estimated; and the length of the known signal data group is the same as that of the signal sequence to be estimated.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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