Transiently chaotic neural networks with piecewise linear output functions |
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| Authors: | Shyan-Shiou Chen Chih-Wen Shih |
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| Institution: | 1. College of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China;2. Department of Computer and Information Science, University of Macau, Macau 999078, China;3. School of Sciences, Beijing University of Posts and Telecommunications, Beijing 100876, China;1. Department of Engineering Science, Kermanshah University of Technology, Kermanshah, Iran;2. Department of Mathematics, Faculty of Engineering and Natural Sciences,Bahçe?ehir University, Istanbul 34349, Turkey;3. Department of Mathematics, National Institute of Technology, Jamshedpur, Jharkhand 831014, India |
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| Abstract: | Admitting both transient chaotic phase and convergent phase, the transiently chaotic neural network (TCNN) provides superior performance than the classical networks in solving combinatorial optimization problems. We derive concrete parameter conditions for these two essential dynamic phases of the TCNN with piecewise linear output function. The confirmation for chaotic dynamics of the system results from a successful application of the Marotto theorem which was recently clarified. Numerical simulation on applying the TCNN with piecewise linear output function is carried out to find the optimal solution of a travelling salesman problem. It is demonstrated that the performance is even better than the previous TCNN model with logistic output function. |
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