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Signal robust sparse time-frequency analysis method, terminal equipment and storage medium

A time-frequency analysis and signal technology, applied in the field of signal processing, can solve problems such as the inability to accurately reflect the effective signal spectrum distribution, noise interference, etc.

Pending Publication Date: 2022-01-14
MINNAN NORMAL UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the sparse time-frequency analysis method can accurately describe the spectrum of the effective signal, it cannot reflect the spectrum distribution of the effective signal more accurately for noise interference, especially under the impact noise interference.

Method used

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  • Signal robust sparse time-frequency analysis method, terminal equipment and storage medium
  • Signal robust sparse time-frequency analysis method, terminal equipment and storage medium
  • Signal robust sparse time-frequency analysis method, terminal equipment and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0060] Firstly, the preliminary knowledge related to this embodiment is introduced.

[0061] (1) Sparse time-frequency analysis model

[0062] figure 1 The process of short-time Fourier transform weighting sub-signals with a sliding window is shown. figure 1 medium signal sub signal sliding window The signal can be decomposed through a short-term sliding window, so as to obtain the spectral distribution of the local time of the signal.

[0063] figure 1 in order Represents the weighted sub-signal, the starting point of sparse time-frequency analysis is to find a sparse solution of the spectrum in the frequency domain Make the spectrum satisfy the following formula:

[0064]

[0065] in, is a sparse transformation matrix, S=[I|O] is a truncation matrix, and its function is to obtain the inversion signal The first M points of , is the identity matrix, represents a matrix with all zero elements, Represents the Fourier transform matrix, Indicates the ...

Embodiment 2

[0188] The present invention also provides a signal robust sparse time-frequency analysis terminal device, including a memory, a processor, and a computer program stored in the memory and operable on the processor, and the processor executes the computer program The steps in the above method embodiment of Embodiment 1 of the present invention are realized at the same time.

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Abstract

The invention relates to a signal robust sparse time-frequency analysis method, terminal equipment and a storage medium. The method comprises the following steps: S1, constructing a signal impact noise removal model based on morphological component analysis, sparse time-frequency analysis and frame wavelet transform; S2, for the signal impact noise removal model, calculating a texture component yT and a cartoon component yC of the signal after impact noise removal by using a forward decomposition method; and S3, according to the texture component yT and the cartoon component yC of the signal, calculating a spectrum sparse solution xi after the signal impact noise is removed by using a backward decomposition method for the signal impact noise removal model. According to the method, a morphological component analysis algorithm is introduced to decompose a signal to be processed into a low-frequency cartoon component, a high-frequency texture component and a noise component, and a stationary frame wavelet regular term is further introduced on the basis of morphological component analysis, so that the difference between a signal effective component and the noise component is fully mined, and the purposes of noise suppression and robust time-frequency analysis are achieved.

Description

technical field [0001] The invention relates to the field of signal processing, in particular to a signal robust sparse time-frequency analysis method, terminal equipment and a storage medium. Background technique [0002] The time-frequency analysis method can effectively reflect the spectral distribution of the signal at local time. It is an important research branch in the field of signal processing and is widely used in geophysical exploration, radar imaging, mechanical vibration signal analysis, biomedical signal analysis, power signal analysis, etc. field. However, traditional time-frequency analysis methods have problems such as insufficient resolution and cross-term interference. [0003] In recent years, with the rise of sparse representation and the continuous maturity and improvement of optimization theory, the sparse time-frequency analysis method based on sparse representation has begun to appear, which solves the problem of insufficient resolution of time-freq...

Claims

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Application Information

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IPC IPC(8): G06F30/27G06K9/62G06F119/10
CPCG06F30/27G06F2119/10G06F18/214
Inventor 陈颖频王海光王灵芝喻飞林凡陈育群宋建华何丽陈悦
Owner MINNAN NORMAL UNIV
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