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Abstract In this paper, the exponential input-to-state stability (ISS) for complex-valued memristor-based bidirectional associative memory (BAM) neural networks with multiple time-varying delays is discussed. By constructing a novel Lyapunov functional… Click to show full abstract
Abstract In this paper, the exponential input-to-state stability (ISS) for complex-valued memristor-based bidirectional associative memory (BAM) neural networks with multiple time-varying delays is discussed. By constructing a novel Lyapunov functional and utilizing inequality techniques, a sufficient criterion of the exponential input-to-state stability for the considered system is firstly derived. Moreover, similar result is also obtained for delayed complex-valued BAM neural networks without memristors. Finally, two numerical examples are given to demonstrate the effectiveness of the obtained results.
Journal Title: Neurocomputing
Year Published: 2018
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