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Cao, Jinde; Chen, Tianping

Globally exponentially robust stability and periodicity of delayed neural networks. (English) Zbl 1061.94552

Chaos Solitons Fractals 22, No. 4, 957-963 (2004).
Summary: A new concept of robust periodicity is introduced, and the problem of robust stability and robust periodicity is discussed for delayed neural networks. Several sufficient conditions are derived for globally exponentially robust stability and robust periodicity of delayed neural networks based on the Lyapunov method. These results improve and extend those given in the earlier references.

Cited in 72 Documents

MSC:

94C05 Analytic circuit theory
68T05 Learning and adaptive systems in artificial intelligence
93D20 Asymptotic stability in control theory
93C10 Nonlinear systems in control theory
34D05 Asymptotic properties of solutions to ordinary differential equations
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\textit{J. Cao} and \textit{T. Chen}, Chaos Solitons Fractals 22, No. 4, 957--963 (2004; Zbl 1061.94552)
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References:

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