Abstract
This paper is concerned with fuzzy bidirectional associative memory (BAM) Cohen-Grossberg neural networks with mixed delays and impulses. By constructing an appropriate Lyapunov function and a new differential inequality, we obtain some sufficient conditions which ensure the existence and global exponential stability of a periodic solution of the model. The results in this paper extend and complement the previous publications. An example is given to illustrate the effectiveness of our obtained results.
Highlights
In recent years, considerable attention has been paid to bidirectional associative memory (BAM) Cohen-Grossberg neural networks [ ] due to their potential applications in various fields such as neural biology, pattern recognition, classification of patterns, parallel computation and so on [ – ]
Numerous application examples appear, for example, emerging parallel/distributed architectures were explored for the digital VLSI implementation of adaptive bidirectional associative memory (BAM) [ ], Teddy and Ng [ ] applied a novel local learning model of the pseudo self-evolving cerebellar model articulation controller (PSECMAC) associative memory network to produce accurate forecasts of ATM cash demands
The main purpose of this paper is to investigate the existence and global exponential stability of a periodic solution of fuzzy BAM Cohen-Grossberg neural networks with mixed delays and impulses
Summary
Considerable attention has been paid to bidirectional associative memory (BAM) Cohen-Grossberg neural networks [ ] due to their potential applications in various fields such as neural biology, pattern recognition, classification of patterns, parallel computation and so on [ – ]. There are rare papers that consider exponential stability of this kind of fuzzy bidirectional associative memory CohenGrossberg neural networks with mixed delays and impulses. Inspired by the discussion above, in this paper, we are to consider the following fuzzy bidirectional associative memory Cohen-Grossberg neural networks with mixed delays and impulses,. The main purpose of this paper is to investigate the existence and global exponential stability of a periodic solution of fuzzy BAM Cohen-Grossberg neural networks with mixed delays and impulses. By constructing a suitable Lyapunov function and a new differential inequality, we establish some sufficient conditions to ensure the existence and global exponential stability of a periodic solution of the model In Section , we present some new sufficient conditions to ensure the existence and global exponential stability of a periodic solution of model
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