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On the Dynamical Behaviors of a Class Neural Networks with Time-varying

Author: YuFang
Tutor: JiangHaiJun
School: Xinjiang University
Course: Applied Mathematics
Keywords: Fuzzy cellular neural networks Reaction-diffusion Time Delay Pulse Global exponential synchronization
CLC: TP183
Type: Master's thesis
Year: 2010
Downloads: 43
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Abstract


The neural network has a huge potential for practical applications in many areas , many scholars dedicated to the theoretical study of the neural network , and has achieved many good results . This paper mainly behavioral studies involved three types of neural network model with delays . including : fuzzy cellular neural networks with time delay reaction diffusion study global exponential synchronization ; competitive neural network with time delay reaction diffusion term pulse fuzzy cellular neural networks globally exponentially synchronized research ; Delay with different time scales stability of the index . main content of this paper can be summarized as follows : an Introduction , the first part of the generation of neural network and significance of the subsequent second part describes the various types of mathematical models of neural networks with time neural network research lag . third part given the structure of this organization . discussed in Section 2 with delayed reaction-diffusion fuzzy cellular neural networks global exponential synchronization by using the Lyapunov function method and inequality technique we get a sufficient condition to ensure that the system synchronization , these conditions proliferation in the design time delay neural network synchronization and applications have a very important role . Finally, a numerical example is given to show the effectiveness of the proposed full judgment synchronization conditions . 3 , we focused on a class of global exponential fuzzy cellular neural networks with reaction diffusion term pulse synchronization are analyzed and discussed . Norm under the premise of the norm , by using inequality technique , the global index sufficient conditions for synchronization . Finally, a numerical example is given to illustrate the validity of the results . 4 focuses on a class with different time scales of existence, uniqueness and exponential stability of delayed competitive neural network equilibrium point , we first use of nonsmooth analysis method has been sufficient condition of existence and uniqueness, combined with matrix theory and inequality technique to draw some equilibrium point exponential stability of the equilibrium point . Finally, some numerical examples to show the feasibility and effectiveness of the method .

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