Self-adaptive signal analysis method based on continuous variable variational mode decomposition

A technique of variational mode decomposition and adaptive signal, which is applied in the field of analysis and processing of multivariate data, to achieve the effect of solving mode aliasing, less parameters and low computational complexity

Pending Publication Date: 2021-05-11
LIAOCHENG UNIV
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to decompose the multi-channel signal adaptively, and effectively extract the common modes of the multi-channel signal on different time scales, and realize adaptive filtering and noise removal

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  • Self-adaptive signal analysis method based on continuous variable variational mode decomposition
  • Self-adaptive signal analysis method based on continuous variable variational mode decomposition
  • Self-adaptive signal analysis method based on continuous variable variational mode decomposition

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Embodiment Construction

[0043] Below in conjunction with embodiment, the content of the invention is further described.

[0044] First, use the simulation data to verify the effect of adaptive decomposition, denoising and anti-modal aliasing of the method of the present invention, and then apply the actual EEG signal to verify that the method of the present invention is applicable to the early prediction of epileptic seizures:

[0045] 1. Test the robustness of the algorithm to noise, and compare the decomposition effects of SMVMD and MEMD. Construct a composite cosine signal f with Gaussian white noise 1 and f 2 and the noise-free signal f 3 , whose composition is as follows:

[0046] f 1 =4cos(10πt)+2cos(20πt)+η 1 ,

[0047] f 2 =3cos(10πt)+3cos(50πt)+η 2 ,

[0048] f 3 =2cos(10πt)+3cos(20πt)+4cos(50πt),

[0049] where η 1 and η 2 Gaussian white noise, η 1 ~N(0,0.12), η 2 ~N(0,0.12), the signal waveform is shown in Figure 1(a). In both simulation experiments and real EEG data proces...

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Abstract

The invention discloses a self-adaptive signal analysis method based on continuous variable variational mode decomposition. The method is suitable for self-adaptive decomposition, denoising and filtering of multi-channel stable or non-stable signals. According to the method, a decomposition scale and tedious parameter optimization do not need to be set by priori knowledge, and the multi-channel signals can be continuously and adaptively decomposed into intrinsic modes of different time scales only according to the internal time-frequency domain characteristics of the signals. The method has practical value on denoising, adaptive filtering and mode recognition of multi-variable signals in engineering.

Description

technical field [0001] The present invention relates to the analysis and processing of multi-variable data, especially the analysis of non-stationary signals, precisely decomposing the common eigenmodes of multi-channel signals so as to realize a preprocessing method for signals. Background technique [0002] The statistics of non-stationary signals are functions that vary with time, and the frequency of the signal varies with time. Non-stationary signals exist widely in the real world, whether engineering signals, biological signals, medical signals, or statistical data in economics are non-stationary, so the processing and research of non-stationary signals is of great significance. [0003] Because the frequency of a non-stationary signal varies with time, the characteristics of the signal must be analyzed from both the time domain and the frequency domain. Common signal decomposition methods include Fourier transform, wavelet transform, empirical mode decomposition (EMD...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06F2218/02G06F2218/00
Inventor 张婷琳乔立山吴晓
Owner LIAOCHENG UNIV
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