Supercharge Your Innovation With Domain-Expert AI Agents!

Judgment method for iteration state of adaptive filtering algorithm

An adaptive filter and algorithm technology, applied in the field of signal processing, can solve the problems of difficult definition of standards, inability to accurately judge the iterative state of the system, large iterative errors, etc., and achieve the effects of strong adaptability, clear convergence and divergence, and small errors

Pending Publication Date: 2021-12-17
西安艾科特声学科技有限公司
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

If the expected response itself is large, even if the system convergence state is good, the iteration error may still be large, which will make it difficult to define the standard for judging the iterative state of the system, so that it is impossible to accurately judge the iterative state of the system

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
  • Judgment method for iteration state of adaptive filtering algorithm
  • Judgment method for iteration state of adaptive filtering algorithm
  • Judgment method for iteration state of adaptive filtering algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0035] A method for judging the iterative state of an adaptive filtering algorithm, specifically as follows:

[0036] First, sort out the principle of adaptive filtering algorithm.

[0037] according to figure 1 , for a certain moment, the input signal is x(n), the expected response is d(n), the output response of x(n) after passing through the filter is y(n), and the difference e(n) between the two is the iterative error.

[0038] Let the filter estimation model be then there is

[0039]

[0040] In formula (1), x(n)=(x(n)...x(n-L+1)) T , where L is the filter length.

[0041] When the iteration error is expected to be zero, that is, when E{e(n)}=0, there is y(n)=d(n), and the filter iteration state is optimal at this time.

[0042] Let J(n)=e 2 (n), then there are

[0043]

[0044] Formula (2) pairs Seek the partial derivative, then there is

[0045]

[0046] Assuming that the iteration coefficient of the algorithm is μ, then we have

[0047]

[004...

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 method for judging the iteration state of a self-adaptive filtering algorithm. The method comprises the following steps: firstly, carrying out the combing according to the principle of the self-adaptive filtering algorithm; and establishing a filter estimation model. Finally, the system iteration state can be accurately judged according to the calculation result, and the judgment standard is as follows: after algorithm iteration is stable, if V (n) is smaller than 0, the algorithm converges, and if V (n) is larger than 0, the algorithm diverges. The method has the technical effects and advantages that the iteration state of the adaptive filtering system can still be judged through iteration errors, the judgment result of the method provided by the invention is more accurate, the definition standard of convergence and divergence is very clear, and errors are smaller.

Description

technical field [0001] The invention relates to the technical field of signal processing, in particular to a method for judging the iterative state of an adaptive filtering algorithm. Background technique [0002] The main task of signal processing is to solve the problem of signal extraction from noise. When the input signal is disturbed by noise, the output terminal still needs to accurately reproduce the signal while suppressing the influence of noise to the greatest extent. The above problems can be solved by adaptive filters. The adaptive filter is the optimal filter based on the criterion of the minimum mean square error, which can automatically adjust its own unit impulse response to achieve the optimum. Adaptive filtering includes two parts: filter and algorithm. The filter is the hardware platform to complete the filtering task, and the algorithm is used to adjust the filter impulse response or transfer function. [0003] For this kind of adaptive filtering system,...

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
Patent Type & Authority Applications(China)
IPC IPC(8): H03H21/00
CPCH03H21/0043
Inventor 李荣玉昊昕代海王金林宁晓峰龙拉怀
Owner 西安艾科特声学科技有限公司
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com