Nerve computing model for solving matrix equation set

A technology for computing models and matrix equations, applied in the field of neural computing models, can solve problems such as violation of real-time computing, time-consuming, time-varying matrix solution errors, etc.

Inactive Publication Date: 2017-11-24
QUFU NORMAL UNIV
View PDF0 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, the time-varying matrix solution obtained by ZNN without considering the influence of noise has a large error with the actual situation, and even leads to

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
  • Nerve computing model for solving matrix equation set
  • Nerve computing model for solving matrix equation set

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] The present invention will be further described below.

[0018] A method for constructing a neural computing model for solving matrix equations, comprising the steps of:

[0019] a) Define the error function E(t) of the matrix value according to the design method of Zhang Neural Network, where E(t)=A(t)X(t)-B(t), where A(t), B(t ) is a known stable time-varying coefficient matrix, X(t) is an unknown time-varying coefficient matrix to be solved, and t is time;

[0020] b) According to Zhang neural network design formula get deformed

[0021] c) definition Find the derivative of e according to the mathematical derivation formula make get

[0022] d) will bring in get in

[0023] e) the formula Shift to get where k 1 =k 2 = 1, F(E(t)) and are activation functions;

[0024] f) Obtain the derivative of the error function E(t) according to the mathematical derivation formula Will substitute The model formula is obtained in: ,in It i...

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

A method for constructing a neural computing model for solving matrix equations, the formula of which is: A ( t ) X ( t ) · = - A · ( t ) X ( t ) + B · ( t ) - F ( A ( t ) X ( t ) - B ( t ) ) - G ( A ( t ) X ( t ) - B ( t ) + ∫ 0 t F ( A ( t ) X ( t ) - B ( t ) ) d t ) + W ( t ) Calculate the solved X(t) through this final formula, starting from any initial state X(0)∈Rn×m, which is equivalent to the state matrix of the time-varying theoretical solution, and each of their elements is a monotonically increasing odd activation function . The neural computing model for solving matrix equations of the present invention has the characteristics of converging to the theoretical solution of matrix equations in a limited time even under the pollution of noise (constant noise, random noise), and no matter what activation function is used, the present invention The invention can converge to the theoretical solution of matrix equations.

Description

technical field [0001] The invention relates to the fields of matrix equations and neural networks, in particular to a neural calculation model for solving matrix equations. Background technique [0002] The problem of systems of linear matrix equations has been extensively studied in academia and industry in recent years, and has found applications in mathematics, system control, robotics, and other fields. Due to its huge potential academic value and practical value, finding a fast and effective solution to linear matrix engineering has become one of the directions that many researchers are striving to achieve. Therefore, many related algorithms have been proposed and discussed, and good research results have been obtained. However, it is a pity that these proposed algorithms for serial processing are not suitable for time-varying linear matrices due to the shortcoming of requiring related iterative algorithms to be completed within a single sampling period. [0003] Rec...

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): G06F17/16G06N3/04
CPCG06F17/16G06N3/04
Inventor 禹继国李晓晓李帅
Owner QUFU NORMAL UNIV
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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap