Abstract
In this paper, passivity analysis of fractional-order neutral-type fuzzy cellular bidirectional associative memory (BAM) neural networks with time-varying delays is investigated. Based on the Lyapunov–Krasovskii functional, delay-dependent sufficient conditions for solvability of the passive problem are obtained in terms of linear matrix inequalities (LMIs), which can be easily checked by using the MATLAB LMI toolbox. Finally, numerical examples are provided to show the effectiveness of the main results.
Highlights
E neural network model having time delays in the time derivatives of states is called delayed neutral-type neural networks. e neutral-type system characterizes the dynamic property of the system state and describes the dynamic varying rule of the delay state of the system
Many neural networks can be regarded as special cases of neutral neural networks, and most of the neural networks can be transformed into neutral neural networks for research [29, 30]
Mathematical Problems in Engineering fuzzy cellular neural networks have their potential in image processing and pattern recognition, and a few outcomes have been discussed [36–41]
Summary
E neural network model having time delays in the time derivatives of states is called delayed neutral-type neural networks. e neutral-type system characterizes the dynamic property of the system state and describes the dynamic varying rule of the delay state of the system. Stability criteria for neutral-type BAM neural networks with time delays were derived in [31–34]. Inspired by the above discussions, the problem of passivity-based fractional-order neutral-type fuzzy cellular BAM neural networks with time-varying delays is examined in this paper.
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