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

Signal blind detection method based on double sigmoid hysteresis noise chaotic neural network

A neural network, blind detection technology, applied in the direction of transmission modification based on link quality, device dedicated to receiver, shaping network in transmitter/receiver, etc., can solve the problem of slow energy function convergence speed, etc. Achieve the effect of excellent convergence speed, excellent anti-noise performance, and enhanced optimization performance

Active Publication Date: 2021-06-11
NANJING UNIV OF POSTS & TELECOMM +1
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, TCHNN has negative self-coupling, which will lead to slower convergence of the energy function

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
  • Signal blind detection method based on double sigmoid hysteresis noise chaotic neural network
  • Signal blind detection method based on double sigmoid hysteresis noise chaotic neural network
  • Signal blind detection method based on double sigmoid hysteresis noise chaotic neural network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0059] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.

[0060] The present invention proposes the signal blind detection method based on double Sigmoid hysteresis noise chaotic neural network, and its implementation process is as follows:

[0061] When ignoring noise, the receiver equation for a discrete-time channel is defined as

[0062] x N =SΓ T

[0063] (1)

[0064] In the formula, X N is the receiving data matrix, S is the sending signal matrix, Γ is the channel impulse response h jj Constituted block Toeplitz matrix; ( ) T Represents matrix transposition;

[0065] Among them, the sending signal matrix:

[0066] S=[s L+M (k),L,s L+M (k+N-1)] T =[s N (k),L,s N (k-M-L)] N×(L+M+1) ,

[0067] M is the channel order, L is the equaliz...

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 signal blind detection method based on double sigmoid hysteresis noise chaotic neural network, which is characterized by comprising the following steps: step SS1: constructing a received data matrix X N ; Step SS2: to the received data matrix X N Perform singular value decomposition; Step SS3: Set the weight matrix W; Step SS4: Select the activation function of the double Sigmoid hysteresis chaotic neural network, perform the iterative operation of the double Sigmoid hysteresis chaotic neural network, and then substitute the result of each iteration into the double Sigmoid hysteresis noise chaos In the energy function E(t) of the neural network, when the energy function E(t) reaches the minimum value, the dual Sigmoid hysteresis noise chaotic neural network reaches equilibrium, and the iteration ends. The invention uses the dual Sigmoid chaotic neural network and hysteresis noise to form a dual Sigmoid hysteresis noise chaotic neural network for the first time, which enhances the optimization performance of the network and improves the quality of the network optimization solution. The anti-noise performance and convergence speed of the invention are better than those of the traditional The Hopfield signal blind detection algorithm.

Description

technical field [0001] The invention relates to a signal blind detection method based on a double-Sigmoid hysteresis noise chaotic neural network, and belongs to the technical field of wireless communication signal processing and neural network. Background technique [0002] The rapid development of data communication and wireless sensor network technology has put forward higher requirements for the blind detection of communication signals (BlindDetection). The so-called blind detection means that only the received signal itself can be used to detect the transmitted signal, thereby eliminating inter-signal interference (ISI) to improve the information transmission rate and reliability. [0003] In order to solve the problem of poor signal transmission quality and poor anti-interference ability caused by improving genetic, ant colony, immune, particle swarm and other intelligent algorithms, many literatures have begun to use Hopfield neural network to study the problem of bli...

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): H04L25/03H04L1/00
CPCH04L1/0038H04L25/03165
Inventor 张昀于舒娟李冰蕊陈少威杨杰曹建
Owner NANJING UNIV OF POSTS & TELECOMM
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