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Research on Chaotic Neural Network and Its Application

Author: DaiMinMin
Tutor: LiuJianXia
School: Taiyuan University of Technology
Course: Circuits and Systems
Keywords: Neural Networks Transiently chaotic neural network Traveling Salesman Problem Broadband matching network Real frequency method
CLC: TP183
Type: Master's thesis
Year: 2010
Downloads: 163
Quote: 1
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Abstract


The artificial neural network is a new kind of information processing system based on a preliminary understanding of the human brain tissue structure, activities mechanism proposed. By mimicking the organizational structure of the brain systems as well as some of the activities of the mechanism of the artificial neural network can exhibit many of the characteristics of the human brain, and has some of the basic functions of the human brain. In recent years, it was discovered that there are many irregular chaotic phenomena in the nervous system, so the chaotic neural network (CNN) has become a new task placed in front of the people. In this paper, a chaotic neural network as the main object of study, and applied to a typical combinatorial optimization problem solving and broadband matching network designs. The research content of this paper is divided into two parts, the first, chaotic dynamics, the classic Hopfield neural network and chaotic neural network theory; chaotic neural network applied research. Including the following parts: (1) system introduces the basic theory of chaotic dynamics, given the chaos of the basic definitions of basic terminology and the basic characteristics of a typical chaotic map - Logistic mapping example, a detailed analysis of the Lyapunov exponent and the chaotic state of the relationship, to verify the validity of the basic chaotic algorithm with the classic function. (2) summarize several chaotic neural network model, which transiently chaotic neural network (TCNN) model has been improved, and for the simulation of complex nonlinear function test, simulation results with the classical Hopfield neural network algorithm simulation results comparison, this paper improved transiently chaotic neural network is proved effective. Energy function (3) derived Hopfield neural networks for solving the traveling salesman problem (TSP), the TSP problem Hopfield neural network and Hopfield neural network and transiently chaotic neural network two algorithms for both 10 city ??TSP problem solving, simulation results show the superiority of transiently chaotic neural network method in solving TSP. (4) introduction the broadband matching process of the development of the theory of knowledge and analysis of the real frequency method in the computer-aided method. Transiently chaotic neural network-based broadband matching design, combined with the actual antenna sub-objective function, and optimize the antenna matching network integrated by the optimization results, the simulation curve illustrates the design optimization The matching network is valid.

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory > Artificial Neural Networks and Computing
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