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A signal noise reduction method based on variational mode decomposition and a minimum mean square error adaptive filter

A variational modal decomposition, minimum mean square error technology, applied in instruments, character and pattern recognition, computer parts and other directions, can solve the problems of modal aliasing, false components of modal functions, etc.

Active Publication Date: 2019-03-08
NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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Problems solved by technology

Although simple to implement, the resulting modal functions are prone to spurious components and modal aliasing

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  • A signal noise reduction method based on variational mode decomposition and a minimum mean square error adaptive filter
  • A signal noise reduction method based on variational mode decomposition and a minimum mean square error adaptive filter
  • A signal noise reduction method based on variational mode decomposition and a minimum mean square error adaptive filter

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[0045] Taking a noise-containing signal with a signal-to-noise ratio of -20dB as an example below, the present invention will be further described in conjunction with the accompanying drawings. In this example, Gaussian white noise is used as the noise. In order to illustrate the superiority of this method, the noise-containing signals with different signal-to-noise ratios are compared before and after noise reduction.

[0046] The foregoing embodiment includes the following steps:

[0047] Step A: At the sampling frequency f s Obtain the discrete noisy signal s(l) to be processed and the discrete noise signal n with the same statistical properties 0 (l), s(l) and n 0 The data lengths of (l) are all L, (1≤l≤L). Set the sampling frequency to f s =500kHz, the data length is L=1000, i.e. 1000 sampling points, the time-domain waveform and corresponding frequency spectrum diagram of s(l) are as figure 2 shown.

[0048] Step B: Use the minimum mean square error adaptive filte...

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Abstract

The invention provides a noise reduction method based on variational mode decomposition and a minimum mean square error adaptive filter. This method combines the advantages of variational modal decomposition and least mean square adaptive filter, the noisy and noisy signals are decomposed into K eigenmode components by using variational mode decomposition algorithm, and then each eigenmode component is filtered by least mean square adaptive filter. Finally, the denoised signal is reconstructed from the K filtering results. This method not only has good function of signal-noise separation, butalso can effectively suppress the phenomenon of mode aliasing. The adaptive filter can automatically adjust the filter parameters iteratively to meet the requirements of certain criteria, so as to achieve optimal filtering, has and have the function of self-tuning and tracking.

Description

technical field [0001] The invention relates to a noise reduction method for narrowband signals, in particular to a signal noise reduction method based on variational mode decomposition and minimum mean square error adaptive filter. Background technique [0002] The noise reduction problem is a classic problem in the field of signal processing. Many methods have been proposed for the noise reduction problem at home and abroad, and many achievements have been made. [0003] American scholar Huang first proposed empirical mode decomposition in 1998, which is used to decompose the original signal sequence into a limited number of intrinsic mode function components and a residual component, which is very suitable for the analysis of non-stationary signals. Although simple to implement, the resulting modal functions are prone to spurious components and modal aliasing. [0004] The decomposition results of the variational mode decomposition proposed in 2014 are similar to the emp...

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Application Information

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IPC IPC(8): G06K9/00
CPCG06F2218/06
Inventor 邵杰周凡
Owner NANJING UNIV OF AERONAUTICS & ASTRONAUTICS
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