A Nonlinear Volterra Filter Optimization Method Based on Contribution Factor

An optimization method and nonlinear technology, applied in impedance networks, digital technology networks, electrical components, etc., can solve the problems of reducing the amount of calculation and large amount of calculation in filtering processing, so as to reduce the amount of calculation, wide applicability, and improve engineering. The effect of realizing the possibility

Active Publication Date: 2018-04-10
XIAN INSTITUE OF SPACE RADIO TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art, and provides a nonlinear Volterra filter optimization method based on contribution factors. This method aims at the problem of large amount of calculation in the existing nonlinear Volterra filter method, and proposes to output according to each node The contribution of the signal, find and delete redundant nodes, so as to reduce the calculation amount of filtering processing, realize filtering optimization, and facilitate the engineering realization of nonlinear Volterra filtering

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
  • A Nonlinear Volterra Filter Optimization Method Based on Contribution Factor
  • A Nonlinear Volterra Filter Optimization Method Based on Contribution Factor
  • A Nonlinear Volterra Filter Optimization Method Based on Contribution Factor

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0027] The present invention will be further described below with reference to the drawings and embodiments.

[0028] The present invention searches for redundant nodes of the nonlinear Volterra filter based on the size of the contribution factor, and realizes the optimization of the filtering method by shielding the redundant nodes, which can effectively reduce the calculation amount of the filtering realization. Among them, there are two types of contribution factors involved in the present invention: one is absolute contribution factor, and the other is relative contribution factor. The definitions of contribution factors and optimization methods based on the two contribution factors are described in detail below.

[0029] (1) Definition of contribution factor

[0030] Based on long-term research and analysis, the present invention proposes the definition of contribution factor for the first time in the field of signal processing.

[0031] Definition 1: Absolute contribution factor...

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 non-linear Volterra filtering optimization method based on a contribution factor, and the method comprises the steps: 1, obtaining an original output signal of a non-linear Volterra filter; 2, setting the weighting coefficient of each node of the non-linear Volterra filter as zero, forming sub-filters, and obtaining an output signal of each sub-filter; 3, calculating the contribution factor of each node according to the output signal and the original output signal of each sub-filter; 4, comparing the contribution factor of each node with a set threshold value delta, and determining the optimal weighting coefficient of the non-linear Volterra filter; 5, forming an optimized filter according to the optimal weighting coefficient. The method aims at a problem that a conventional non-linear Volterra filtering method is large in calculation burden, proposes a method for searching and deleting the redundant nodes according to the attribution of each node to the corresponding output signal, deletes the redundant nodes with the minimum contribution to the output result under the condition that the filtering performance is not affected, can further reduce the calculation amount, and reduces the occupied resource of engineering implementation.

Description

Technical field [0001] The present invention relates to the technical field of nonlinear Volterra filtering, in particular to a nonlinear Volterra filtering optimization method based on contribution factors. Background technique [0002] The current research proves that under the condition that the input signal energy is limited, the description of the nonlinear system can be arbitrarily approximated by Volterra series. Therefore, the nonlinear Volterra filtering technology has become an effective nonlinear signal processing method. Simple and convenient to operate, it is highly valued in the existing filtering technology field. At present, Volterra filtering technology has been successfully applied to many engineering fields, such as nonlinear system control, radio communication, satellite communication, magnetic tape channel, and biological process modeling. [0003] However, the existing nonlinear Volterra filtering method has the defects of large amount of calculation and larg...

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 Patents(China)
IPC IPC(8): H03H17/02
CPCH03H17/0261
Inventor 马文强邱伟峰孙洋禚国维马伟张舸李杰
Owner XIAN INSTITUE OF SPACE RADIO TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products