Multiperiodicity and exponential attractivity evoked by periodic external inputs in delayed cellular neural networks. (English) Zbl 1107.68086

Summary: We show that an \(n\)-neuron cellular neural network with time-varying delay can have \(2^n\) 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.


68T05 Learning and adaptive systems in artificial intelligence
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