Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Wavelet denoising method for adaptively determining wavelet hierarchical series

A wavelet denoising and self-adaptive technology, applied in the field of radar and sonar, can solve the problems of cumbersome process and low efficiency of decomposition layer determination, and achieve the effect of solving the cumbersome operation process and simplifying the wavelet denoising method

Active Publication Date: 2019-12-20
HOHAI UNIV
View PDF4 Cites 12 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the deficiencies of the prior art, the purpose of the present invention is to provide a wavelet denoising method for adaptively determining the wavelet layered series, so as to solve the problem of low efficiency and cumbersome process of determining the decomposition layer existing in the prior art

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Wavelet denoising method for adaptively determining wavelet hierarchical series
  • Wavelet denoising method for adaptively determining wavelet hierarchical series
  • Wavelet denoising method for adaptively determining wavelet hierarchical series

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0077] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to more clearly illustrate the technical scheme of the present invention, but cannot limit the protection scope of the present invention with this. 1. Wavelet noise reduction based on spectrum analysis to determine the number of decomposition layers

[0078] A one-dimensional signal model including noise can be expressed as follows:

[0079] x(t)=s(t)+n 0 (t) (1-1)

[0080] In the formula, s(t) is the real signal, n 0 (t) is a noise signal. Processing flow such as figure 1 Shown:

[0081] Depend on figure 1 It can be seen that the wavelet noise reduction process of one-dimensional signal based on spectrum analysis to determine the number of decomposition layers is roughly divided into six steps:

[0082] (1) Selection of wavelet basis functions. According to the original signal to obtain the wavelet basis function, selecting ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a wavelet denoising method for adaptively determining wavelet hierarchical series. The method comprises the following steps: acquiring a wavelet basis function according to anoriginal signal; obtaining a decomposition layer number according to the original signal and a wavelet basis function; decomposing the original signal according to the number of decomposition layers to obtain wavelet coefficients of each layer; determining a threshold value of the wavelet coefficient of each layer according to the wavelet coefficient; performing quantization processing on the wavelet coefficient of each layer; and reconstructing the wavelet coefficient subjected to quantization processing to obtain a denoised signal. A spectral analysis method is adopted, the optimal decomposition layer number is determined in a self-adaptive mode, and the problem that the operation process is tedious when a trial-and-error method is adopted is solved.

Description

technical field [0001] The invention belongs to the technical field of radar and sonar, in particular to a wavelet denoising method for adaptively determining wavelet hierarchical progression. Background technique [0002] Traditional signal denoising processing is mainly based on the method of Fourier transform. After performing Fourier transform on the noisy signal, the noisy signal is converted from the time domain to the frequency domain, and then some frequency domain segments on the frequency domain are The frequency is filtered out, and finally the denoised signal is obtained by inverse Fourier transform. For stationary signals, the noise reduction method based on Fourier transform has a good noise reduction effect, but the effect is poor for non-stationary signals. The wavelet analysis method not only solves the problem of fixed resolution of Fourier transform, but also analyzes the detailed characteristics of the signal, and can better deal with the noisy non-stati...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F17/10
CPCG06F17/10Y02D30/70
Inventor 王峰胡江湖
Owner HOHAI UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com