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A denoising method based on improved wavelet threshold function

A wavelet threshold and function technology, applied in instruments, character and pattern recognition, computer parts, etc., can solve the problems of soft threshold function distortion and hard threshold function discontinuity.

Inactive Publication Date: 2019-03-01
HENAN UNIV OF SCI & TECH
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Problems solved by technology

[0008] In order to overcome the problems of the discontinuous hard threshold function and the distortion of the soft threshold function in the wavelet threshold noise reduction method in the prior art, the present invention provides a noise reduction method based on the improved wavelet threshold function, which solves the above problems through the improved wavelet threshold function

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  • A denoising method based on improved wavelet threshold function
  • A denoising method based on improved wavelet threshold function
  • A denoising method based on improved wavelet threshold function

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Embodiment Construction

[0041] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0042] Such as figure 1 , a kind of noise reduction method based on the improved wavelet threshold function, its technical scheme is: comprise the following steps:

[0043] a. Obtain the original signal s(t), perform preliminary processing, and obtain the signal f to be denoised;

[0044] b. Determine the number of decomposition layers l, and set up a wavelet decomposition function to decompose the signal f to be denoised in a step;

[0045] c. Use the wavel...

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Abstract

In order to overcome the problems of discontinuous hard threshold function and distortion of soft threshold function in wavelet threshold denoising method of the prior art, the invention provides a denoising method based on improved wavelet threshold function, comprising the following steps: acquiring an original signal; determining the number of decomposition layers, establish wavelet decomposition function to decompose the original signal; the detail coefficients of wavelet decomposition coefficients are processed by threshold function, and the improved wavelet detail coefficients are obtained. The approximate coefficients at the bottom of wavelet decomposition and the improved detail coefficients at each layer are reconstructed by wavelet transform, and the de-noised signal is obtainedfinally. The method of the invention can avoid signal oscillation and obtain small signal distortion, and has good application prospect for signal processing.

Description

technical field [0001] The invention provides a signal noise reduction method, which belongs to the field of information technology, relates to wavelet threshold function, wavelet decomposition and wavelet reconstruction theory, and is a noise reduction method based on an improved wavelet threshold function. Background technique [0002] Signal denoising techniques are fundamental steps in signal analysis. The commonly used noise reduction method in practical engineering is the signal noise reduction method based on Fourier transform. Fourier transform is suitable for compressing or filtering signals with approximate periodicity, but for signals with significant local features, the noise reduction effect of this method is not good in applications that require simultaneous analysis of frequency domain and time domain mutation information. [0003] Wavelet analysis is a multi-resolution time-frequency analysis method, which has good local characteristics and multi-resolution ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06F2218/06
Inventor 张各各李刚伟曾波王川川张超
Owner HENAN UNIV OF SCI & TECH
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