Exponential Stability of Switched Neural Networks with Partial State Reset and Time-Varying Delays

Han Pan, Wenbing Zhang () and Luyang Yu
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Han Pan: School of Mathematical Sciences, Yangzhou University, Yangzhou 225002, China
Wenbing Zhang: School of Mathematical Sciences, Yangzhou University, Yangzhou 225002, China
Luyang Yu: School of Mathematical Sciences, Yangzhou University, Yangzhou 225002, China

Mathematics, 2022, vol. 10, issue 20, 1-20

Abstract: This paper mainly investigates the exponential stability of switched neural networks (SNNs) with partial state reset and time-varying delays, in which partial state reset means that only a fraction of the states can be reset at each switching instant. Moreover, both stable and unstable subsystems are also taken into account and therefore, switched systems under consideration can take several switched systems as special cases. The comparison principle, the Halanay-like inequality, and the time-dependent switched Lyapunov function approach are used to obtain sufficient conditions to ensure that the considered SNNs with delays and partial state reset are exponentially stable. Numerical examples are provided to demonstrate the reliability of the developed results.

Keywords: switched systems; Lyapunov function; partial state reset; impulsive systems (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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