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(Neural Computation. 2006;18:848-870.)
© 2006 The MIT Press

Letter

Multiperiodicity and Exponential Attractivity Evoked by Periodic External Inputs in Delayed Cellular Neural Networks

Zhigang Zeng

zhigangzeng{at}163.com School of Automation, Wuhan University of Technology, Wuhan, Hubei, 430070, China

Jun Wang

jwang{at}acae.cuhk.edu.hk Department of Automation and Computer-Aided Engineering, Chinese University of Hong Kong, Shatin, New Territories, Hong Kong

We show that an n-neuron cellular neural network with time-varying delay can have 2n periodic orbits located in saturation regions and these periodic orbits are locally exponentially attractive. In addition, we give some conditions for ascertaining periodic orbits to be locally or globally exponentially attractive and allow them to locate in any designated region. As a special case of exponential periodicity, exponential stability of delayed cellular neural networks is also characterized. These conditions improve and extend the existing results in the literature. To illustrate and compare the results, simulation results are discussed in three numerical examples.




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