CN110188322A - A kind of wave-shape amplitude uncertainty determines method and system - Google Patents
A kind of wave-shape amplitude uncertainty determines method and system Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 65
- 239000011159 matrix material Substances 0.000 claims abstract description 69
- 238000005070 sampling Methods 0.000 claims abstract description 23
- 238000012935 Averaging Methods 0.000 claims abstract description 14
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
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- G06F18/23213—Non-hierarchical techniques using statistics or function optimisation, e.g. modelling of probability density functions with fixed number of clusters, e.g. K-means clustering
Abstract
The present invention discloses a kind of wave-shape amplitude uncertainty and determines method and system, the described method includes: being clustered to obtain first state level and the second state level by multiple sampled points of the k averaging method to waveform, and state vector is obtained according to the first state level and second state level；Sampling point vector is obtained according to the state vector and SYSTEM OF LINEAR VECTOR shift theory, determines the covariance matrix of the sampling point vector；Wave-shape amplitude uncertainty is obtained according to covariance matrix transfer theory and Jacobian matrix, even if the present invention, according to given average waveform and its covariance, can also can accurately calculate the uncertainty of impulse amplitude there are correlated error.
Description
Technical field
The present invention relates to wave-shape amplitude uncertainties to determine technical field.It is not true more particularly, to a kind of wave-shape amplitude
Fixed spend determines method and system.
Background technique
The measurement of impulse waveform is a basic, important measurement demand in electronic instrument field of measuring technique, to existing
The producers and consumers of generally existing digital communication equipment and electronic computer have very great warp in generation life
Ji meaning.Pulse parameter describes the waveform and time domain specification of pulse, is very important electrical parameter, the estimation to pulse parameter
It is the main contents of time domain measurement.With the development of electronic technology, the estimated accuracy of pulse parameter is required higher and higher.Cause
This, determining pulse parameter and carrying out analysis on Uncertainty to it is a highly important job, and pulse parameter mainly includes arteries and veins
Rush amplitude, pulse width, rise time and overshoot etc..
Impulse amplitude is one of parameter index most basic in pulse measure, in signal source and measuring instrument and is
It is also the prerequisite that must be solved in the measurement evaluation of the rise time index of system.Uncertainty is unknown in measured true value
In the case of scientifically illustrate measurement result, currently, the uncertainty analysis method based on statistical theory is widely used.But
It is that current uncertainty analysis method is assuming that pulse parameter error is realized on the basis of all non-relevant, this is false
If being usually correctly, however, irrelevant physical phenomenon can also generate correlation in waveform sometimes.If for example, ignoring
The correlation that multiplying property error generates in state level, the uncertainty of pulse parameter may seriously be over-evaluated.
Summary of the invention
It is an object of the present invention to provide a kind of wave-shape amplitude uncertainties to determine method, even if there is related miss
In the case where difference, according to given average waveform and its covariance, the uncertainty of impulse amplitude can also be accurately calculated.This
Another of invention is designed to provide a kind of wave-shape amplitude uncertainty and determines system.
In order to achieve the above objectives, the present invention adopts the following technical solutions:
The invention discloses a kind of wave-shape amplitude uncertainties to determine method, comprising:
It is clustered to obtain first state level and the second state level by multiple sampled points of the k averaging method to waveform,
And state vector is obtained according to the first state level and second state level；
Sampling point vector is obtained according to the state vector and SYSTEM OF LINEAR VECTOR shift theory, determines the sampling point vector
Covariance matrix；
Wave-shape amplitude uncertainty is obtained according to covariance matrix transfer theory and Jacobian matrix.
Preferably, the waveform is impulse waveform.
Preferably, second state level is the peak level of the impulse waveform.
Preferably, it is clustered to obtain first state level by multiple sampled points of the k averaging method to waveform and be specifically included:
The sampled point of the first quantity is chosen on waveform；
It is ranked up according to sampled point of the range value of sampled point to first quantity；
The reference sample point that the sampled point after sequence is divided into two first areas is determined according to the first quantity；
The range value of the sampled point of two first areas is subtracted each other according to the collating sequence one-to-one correspondence in each region
Obtain the first difference set；
The section for determining corresponding two sampled points of the smallest difference in first difference set is the first most short section；
The first state level is obtained according to the mean value of the range value of the sampled point in the described first most short section.
Preferably, it is clustered to obtain the second state level by multiple sampled points of the k averaging method to waveform and be specifically included:
The sampled point of the second quantity is chosen on waveform；
It is ranked up according to sampled point of the range value of sampled point to second quantity；
The reference sample point that the sampled point after sequence is divided into two second areas is determined according to the second quantity；
The range value of the sampled point of two second areas is subtracted each other according to the collating sequence one-to-one correspondence in each region
Obtain the second difference set；
The section for determining corresponding two sampled points of the smallest difference in second difference set is the second most short section；
Second state level is obtained according to the mean value of the range value of the sampled point in the described second most short section.
Preferably, it is described according to the state vector and SYSTEM OF LINEAR VECTOR shift theory obtain sampling point vector, determine described in
The covariance matrix of sampling point vector specifically includes:
State vector is expressed as to the linear transformation L=H of sampled point vector YLY；
Determine HL, wherein HLI-th of element of the 1st row can indicate are as follows:
HLI-th of element of the 2nd row can indicate are as follows:
According to HLObtain sampled point vector Y.
It is preferably, described that according to covariance matrix transfer theory and Jacobian matrix to obtain wave-shape amplitude uncertainty specific
Include:
Covariance matrix ∑ based on sampling point vectorYCalculate the covariance matrix ∑ of state vector LL；
According to the covariance matrix ∑ of state vector LLWave-shape amplitude uncertainty is obtained with Jacobian matrix.
Preferably, the covariance matrix ∑ based on sampling point vectorYCalculate the covariance matrix ∑ of state vector LLTool
Body includes:
According to HLWith the covariance matrix ∑ of sampling point vectorYObtain the covariance matrix ∑ of state vector LL。
Preferably, the covariance matrix ∑ according to state vector LLIt is uncertain that wave-shape amplitude is obtained with Jacobian matrix
Degree specifically includes:
Wave-shape amplitude is obtained according to first state level and the second state level；
Wave-shape amplitude is directed to the first state level respectively and the second state level derivation obtains Jacobean matrix
Battle array；
According to the covariance matrix ∑ of the Jacobian matrix and the state vector LLObtain wave-shape amplitude uncertainty.
The invention also discloses a kind of wave-shape amplitude uncertainties to determine system, comprising:
State vector determination unit, for being clustered to obtain the first shape by multiple sampled points of the k averaging method to waveform
State level and the second state level, and state vector is obtained according to the first state level and second state level；
Sampled point vector determination unit, for obtaining sampled point arrow according to the state vector and SYSTEM OF LINEAR VECTOR shift theory
Amount determines the covariance matrix of the sampling point vector；
Uncertainty determination unit, for obtaining wave-shape amplitude not according to covariance matrix transfer theory and Jacobian matrix
Degree of certainty.
The present invention is evaluated using uncertainty of the method that impulse waveform covariance matrix transmits to impulse amplitude, should
Method considers the influence of correlated error in waveform, obtained amplitude estimation of uncertainty value all due to the increase of error gradually at
Actual standard deviation for Biased estimator, and pulse parameter is coincide very much, is had universality, can accurately be calculated impulse amplitude
Uncertainty.
Detailed description of the invention
Specific embodiments of the present invention will be described in further detail with reference to the accompanying drawing.
Fig. 1 shows one of the flow chart that a kind of wave-shape amplitude uncertainty of the present invention determines one specific embodiment of method；
Fig. 2 shows two that a kind of wave-shape amplitude uncertainty of the present invention determines the flow chart of one specific embodiment of method；
Fig. 3 shows three that a kind of wave-shape amplitude uncertainty of the present invention determines the flow chart of one specific embodiment of method；
Fig. 4 shows four that a kind of wave-shape amplitude uncertainty of the present invention determines the flow chart of one specific embodiment of method；
Fig. 5 shows five that a kind of wave-shape amplitude uncertainty of the present invention determines the flow chart of one specific embodiment of method；
Fig. 6 shows six that a kind of wave-shape amplitude uncertainty of the present invention determines the flow chart of one specific embodiment of method；
Fig. 7 shows seven that a kind of wave-shape amplitude uncertainty of the present invention determines the flow chart of one specific embodiment of method；
Fig. 8 shows the structure chart that a kind of wave-shape amplitude uncertainty of the present invention determines one specific embodiment of system；
Fig. 9 shows the structural schematic diagram for being suitable for the computer equipment for being used to realize the embodiment of the present invention.
Specific embodiment
In order to illustrate more clearly of the present invention, the present invention is done further below with reference to preferred embodiments and drawings
It is bright.Similar component is indicated in attached drawing with identical appended drawing reference.It will be appreciated by those skilled in the art that institute is specific below
The content of description is illustrative and be not restrictive, and should not be limited the scope of the invention with this.
According to an aspect of the present invention, present embodiment discloses a kind of wave-shape amplitude uncertainties to determine method.Such as Fig. 1
Shown, in the present embodiment, wave-shape amplitude uncertainty determines that method includes:
S100: it is clustered to obtain first state level and the second state by multiple sampled points of the k averaging method to waveform
Level, and state vector is obtained according to the first state level and second state level.
S200: sampling point vector is obtained according to the state vector and SYSTEM OF LINEAR VECTOR shift theory, determines the sampled point
The covariance matrix of vector.
S300: wave-shape amplitude uncertainty is obtained according to covariance matrix transfer theory and Jacobian matrix.
The present invention is evaluated using uncertainty of the method that impulse waveform covariance matrix transmits to impulse amplitude, should
Method considers the influence of correlated error in waveform, obtained amplitude estimation of uncertainty value all due to the increase of error gradually at
Actual standard deviation for Biased estimator, and pulse parameter is coincide very much, is had universality, can accurately be calculated impulse amplitude
Uncertainty.
In a preferred embodiment, the waveform is impulse waveform.When waveform is impulse waveform, second state
Level is the peak level of the impulse waveform.
In a preferred embodiment, as shown in Fig. 2, S100 is gathered by multiple sampled points of the k averaging method to waveform
It is specific that class obtains first state level can include:
S110: the sampled point of the first quantity is chosen on waveform.
S111: it is ranked up according to sampled point of the range value of sampled point to first quantity.
S112: the reference sample point that the sampled point after sequence is divided into two first areas is determined according to the first quantity.
S113: the range value of the sampled point of two first areas is corresponded according to the collating sequence in each region
Subtract each other to obtain the first difference set.
S114: the section for determining corresponding two sampled points of the smallest difference in first difference set is first most short
Section.
S115: the first state level is obtained according to the mean value of the range value of the sampled point in the described first most short section.
Specifically, in a specific example, for first state level L1, the first quantity I can be chosen1(I1It is positive whole
Number) a sampled point, I1A sampled point is expressed as
To I1A sampled point is sorted from small to large, is expressed as
Determine the label of reference sample pointWhereinIt represents less than and is equal to I1/ 2 maximum integer,
To determine reference sample point, the sampled point before reference sample point is a region, including reference sample point and reference sample point
Sampled point later is another region.
With the I after sequence from small to large1The value of sampled point of the sequence more than or equal to h is individually subtracted less than h in a sampled point
Corresponding sequence sampled point value, obtain the set of difference, be expressed as
The section for determining the corresponding sampled point of the smallest difference in the difference set is the first most short section, is expressed as
Determine first state level
In a preferred embodiment, as shown in figure 3, S100 is gathered by multiple sampled points of the k averaging method to waveform
It is specific that class obtains the second state level can include:
S120: the sampled point of the second quantity is chosen on waveform；
S121: it is ranked up according to sampled point of the range value of sampled point to second quantity；
S122: the reference sample point that the sampled point after sequence is divided into two second areas is determined according to the second quantity；
S123: the range value of the sampled point of two second areas is corresponded according to the collating sequence in each region
Subtract each other to obtain the second difference set；
S124: the section for determining corresponding two sampled points of the smallest difference in second difference set is second most short
Section；
S125: second state level is obtained according to the mean value of the range value of the sampled point in the described second most short section.
Specifically, choosing the second quantity I in impulse waveform using k averaging method in a specific example2(I2It is positive whole
Number) a sampled point, I2A sampled point is expressed as
With determining first state level L1Principle it is identical, to I2A sampled point is sorted from small to large.
Choose the label of reference sample pointWhereinIt represents less than and is equal to I2/ 2 maximum is whole
Number, to determine reference sample point, the sampled point before reference sample point is a region, including reference sample point and reference sample
Sampled point after point is another region.
With the I after sequence from small to large2The value of sampled point of the sequence more than or equal to k is individually subtracted less than k in a sampled point
Corresponding sequence sampled point value, obtain the set of difference.
The section for determining the corresponding sampled point of the smallest difference in the difference set is the second most short section, is expressed as
Determine the second state level
In a preferred embodiment, as shown in figure 4, the S200 specifically may include；
S210: state vector is expressed as to the linear transformation L=H of sampled point vector YLY.Pass through state vector L=(L1,
L2)TIndicate first state level and the second state level, then L can be expressed as the linear transformation of sampled point vector Y, i.e. L=
HLY, wherein HLFor the matrix of 2 × I, I=I1+I2。
S220: H is determinedL, wherein HLI-th of element of the 1st row can indicate are as follows:
HLI-th of element of the 2nd row can indicate are as follows:
In a specific example, for impulse form as shown in Figure 1, high level L2For peak value of pulse, HLThe 2nd
I-th capable of element can indicate are as follows:Wherein ymaxFor the maximum value of waveform sampling point Y.
S230: according to HLObtain sampled point vector Y.Sampled point vector Y can be obtained according to matrix theory.
In a preferred embodiment, as shown in figure 5, the S300 is specific can include:
S310: the covariance matrix ∑ based on sampling point vectorYCalculate the covariance matrix ∑ of state vector LL。
According to covariance matrix transfer theory, the covariance matrix of L is represented byWherein ∑LFor L
Covariance matrix, diagonal entry indicate two state level values variance, off diagonal element indicate two state levels
The covariance of value.
S320: according to the covariance matrix ∑ of state vector LLWave-shape amplitude uncertainty is obtained with Jacobian matrix.
In a preferred embodiment, as shown in fig. 6, the S310 is specific can include:
S311: according to HLWith the covariance matrix ∑ of sampling point vectorYObtain the covariance matrix ∑ of state vector LL。
In a preferred embodiment, as shown in fig. 7, the S320 is specific can include:
S321: wave-shape amplitude is obtained according to first state level and the second state level.
Wave-shape amplitude: being directed to the first state level by S322 respectively and the second state level derivation obtain it is refined can
Compare matrix.
S323: according to the covariance matrix ∑ of the Jacobian matrix and the state vector LLIt is not true to obtain wave-shape amplitude
Fixed degree.
Specifically, being defined according to international standard, impulse amplitude A can be indicated are as follows: A=L2-L1, then the side of impulse amplitude A
Difference, as square of the uncertainty of impulse amplitude A, may be expressed as:Wherein, Jacobian matrixUnder normal conditions, JAL=(- 1,1), particularly, for impulse form as shown in Figure 1, high level L2
For definite value, then JAL=(- 1,0)
Based on same principle, the present embodiment also discloses a kind of wave-shape amplitude uncertainty and determines system.As shown in figure 8,
The system comprises state vector determination unit, sampled point vector determination unit and uncertainty determination units.
The state vector determination unit 11 is used to be clustered to obtain by multiple sampled points of the k averaging method to waveform the
One state level and the second state level, and state arrow is obtained according to the first state level and second state level
Amount.
The sampled point vector determination unit 12 according to the state vector and SYSTEM OF LINEAR VECTOR shift theory for being adopted
Sample vector determines the covariance matrix of the sampling point vector.
The uncertainty determination unit 13 is used to obtain waveform according to covariance matrix transfer theory and Jacobian matrix
Amplitude uncertainty.
System, device, module or the unit that above-described embodiment illustrates can specifically realize by computer chip or entity,
Or it is realized by the product with certain function.It is a kind of typically to realize that equipment is computer equipment, specifically, computer is set
It is standby for example can for personal computer, laptop computer, cellular phone, camera phone, smart phone, personal digital assistant,
Media player, navigation equipment, electronic mail equipment, game console, tablet computer, wearable device or these equipment
In any equipment combination.
Computer equipment specifically includes memory, processor and storage on a memory simultaneously in a typical example
The computer program that can be run on a processor is realized when the processor executes described program and is held as described above by client
Capable method, alternatively, the processor realizes the method executed as described above by server when executing described program.
Below with reference to Fig. 9, it illustrates the structural representations for the computer equipment 600 for being suitable for being used to realize the embodiment of the present application
Figure.
As shown in figure 9, computer equipment 600 includes central processing unit (CPU) 601, it can be read-only according to being stored in
Program in memory (ROM) 602 is loaded into random access storage device (RAM) from storage section 608) program in 603
And execute various work appropriate and processing.In RAM603, also it is stored with system 600 and operates required various program sum numbers
According to.CPU601, ROM602 and RAM603 are connected with each other by bus 604.Input/output (I/O) interface 605 is also connected to
Bus 604.
I/O interface 605 is connected to lower component: the importation 606 including keyboard, mouse etc.；It is penetrated including such as cathode
The output par, c 607 of spool (CRT), liquid crystal ultramagnifier (LCD) etc. and loudspeaker etc.；Storage section 608 including hard disk etc.；
And including such as LAN card, the communications portion 609 of the network interface card of modem etc..Communications portion 609 via such as because
The network of spy's net executes communication process.Driver 610 is also connected to I/O interface 606 as needed.Detachable media 611, such as
Disk, CD, magneto-optic disk, semiconductor memory etc. are mounted on as needed on driver 610, in order to read from thereon
Computer program be mounted as needed such as storage section 608.
Particularly, according to an embodiment of the invention, may be implemented as computer above with reference to the process of flow chart description
Software program.For example, the embodiment of the present invention includes a kind of computer program product comprising be tangibly embodied in machine readable
Computer program on medium, the computer program include the program code for method shown in execution flow chart.At this
In the embodiment of sample, which can be downloaded and installed from network by communications portion 609, and/or from removable
Medium 611 is unloaded to be mounted.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
For convenience of description, it is divided into various units when description apparatus above with function to describe respectively.Certainly, implementing this
The function of each unit can be realized in the same or multiple software and or hardware when application.
The present invention be referring to according to the method for the embodiment of the present invention, the process of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
It include so that the process, method, commodity or the equipment that include a series of elements not only include those elements, but also to wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including described want
There is also other identical elements in the process, method of element, commodity or equipment.
It will be understood by those skilled in the art that embodiments herein can provide as method, system or computer program product.
Therefore, complete hardware embodiment, complete software embodiment or embodiment combining software and hardware aspects can be used in the application
Form.It is deposited moreover, the application can be used to can be used in the computer that one or more wherein includes computer usable program code
The shape for the computer program product implemented on storage media (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Formula.
The application can describe in the general context of computer-executable instructions executed by a computer, such as program
Module.Generally, program module includes routines performing specific tasks or implementing specific abstract data types, programs, objects, group
Part, data structure etc..The application can also be practiced in a distributed computing environment, in these distributed computing environments, by
Task is executed by the connected remote processing devices of communication network.In a distributed computing environment, program module can be with
In the local and remote computer storage media including storage equipment.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for system reality
For applying example, since it is substantially similar to the method embodiment, so being described relatively simple, related place is referring to embodiment of the method
Part explanation.
The above description is only an example of the present application, is not intended to limit this application.For those skilled in the art
For, various changes and changes are possible in this application.All any modifications made within the spirit and principles of the present application are equal
Replacement, improvement etc., should be included within the scope of the claims of this application.
Claims (10)
1. a kind of wave-shape amplitude uncertainty determines method characterized by comprising
It is clustered to obtain first state level and the second state level, and root by multiple sampled points of the k averaging method to waveform
State vector is obtained according to the first state level and second state level；
Sampling point vector is obtained according to the state vector and SYSTEM OF LINEAR VECTOR shift theory, determines the association side of the sampling point vector
Poor matrix；
Wave-shape amplitude uncertainty is obtained according to covariance matrix transfer theory and Jacobian matrix.
2. wave-shape amplitude uncertainty according to claim 1 determines method, which is characterized in that the waveform is impulse wave
Shape.
3. wave-shape amplitude uncertainty according to claim 2 determines method, which is characterized in that second state level
For the peak level of the impulse waveform.
4. wave-shape amplitude uncertainty according to claim 1 determines method, which is characterized in that by k averaging method to wave
Multiple sampled points of shape, which are clustered to obtain first state level, to be specifically included:
The sampled point of the first quantity is chosen on waveform；
It is ranked up according to sampled point of the range value of sampled point to first quantity；
The reference sample point that the sampled point after sequence is divided into two first areas is determined according to the first quantity；
The range value of the sampled point of two first areas is subtracted each other to obtain according to the collating sequence one-to-one correspondence in each region
First difference set；
The section for determining corresponding two sampled points of the smallest difference in first difference set is the first most short section；
The first state level is obtained according to the mean value of the range value of the sampled point in the described first most short section.
5. wave-shape amplitude uncertainty according to claim 1 determines method, which is characterized in that by k averaging method to wave
Multiple sampled points of shape, which are clustered to obtain the second state level, to be specifically included:
The sampled point of the second quantity is chosen on waveform；
It is ranked up according to sampled point of the range value of sampled point to second quantity；
The reference sample point that the sampled point after sequence is divided into two second areas is determined according to the second quantity；
The range value of the sampled point of two second areas is subtracted each other to obtain according to the collating sequence one-to-one correspondence in each region
Second difference set；
The section for determining corresponding two sampled points of the smallest difference in second difference set is the second most short section；
Second state level is obtained according to the mean value of the range value of the sampled point in the described second most short section.
6. wave-shape amplitude uncertainty according to claim 1 determines method, which is characterized in that described according to the state
Vector sum SYSTEM OF LINEAR VECTOR shift theory obtains sampling point vector, determines that the covariance matrix of the sampling point vector specifically includes:
State vector is expressed as to the linear transformation L=H of sampled point vector YLY；
Determine HL, wherein HLI-th of element of the 1st row can indicate are as follows:
HLI-th of element of the 2nd row can indicate are as follows:
According to HLObtain sampled point vector Y.
7. wave-shape amplitude uncertainty according to claim 1 determines method, which is characterized in that described according to covariance square
Battle array transfer theory and Jacobian matrix obtain wave-shape amplitude uncertainty and specifically include:
Covariance matrix ∑ based on sampling point vectorYCalculate the covariance matrix ∑ of state vector LL；
According to the covariance matrix ∑ of state vector LLWave-shape amplitude uncertainty is obtained with Jacobian matrix.
8. wave-shape amplitude uncertainty according to claim 6 determines method, which is characterized in that described to be sweared based on sampled point
The covariance matrix ∑ of amountYCalculate the covariance matrix ∑ of state vector LLIt specifically includes:
According to HLWith the covariance matrix ∑ of sampling point vectorYObtain the covariance matrix ∑ of state vector LL。
9. wave-shape amplitude uncertainty according to claim 1 determines method, which is characterized in that described according to state vector
The covariance matrix ∑ of LLWave-shape amplitude uncertainty is obtained with Jacobian matrix to specifically include:
Wave-shape amplitude is obtained according to first state level and the second state level；
Wave-shape amplitude is directed to the first state level respectively and the second state level derivation obtains Jacobian matrix；
According to the covariance matrix ∑ of the Jacobian matrix and the state vector LLObtain wave-shape amplitude uncertainty.
10. a kind of wave-shape amplitude uncertainty determines system characterized by comprising
State vector determination unit obtains first state electricity for being clustered by multiple sampled points of the k averaging method to waveform
Gentle second state level, and state vector is obtained according to the first state level and second state level；
Sampled point vector determination unit, for obtaining sampling point vector according to the state vector and SYSTEM OF LINEAR VECTOR shift theory,
Determine the covariance matrix of the sampling point vector；
Uncertainty determination unit, it is uncertain for obtaining wave-shape amplitude according to covariance matrix transfer theory and Jacobian matrix
Degree.
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