In this paper, exponential stability is studied for a class of high-order bidirectional associative memory (BAM) neural networks with time delays. By employing the linear matrix inequality (LMI) and the Lyapunov functional methods, several sufficient conditions are obtained for ensuring the system to be globally exponentially stable. Two illustrative examples are also given in the end of this paper to show the effectiveness of our results. © 2004 Elsevier B.V. All rights reserved.link_to_subscribed_fulltex
This paper presents a sufficient condition for the existence, uniqueness and global asymptotic stabi...
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This paper presents a sufficient condition for the existence, uniqueness and global asymptotic stabi...
This paper presents some new sufficient conditions for the global robust asymptotic stability of the...
In this paper, a class of generalized bi-directional associative memory (BAM) neural networks with m...
In this paper, global exponential stability and exponential convergence are studied for a class of i...
In this paper, we consider delayed bidirectional associative memory (BAM) neural networks (NNs) with...
This Letter deals with the global exponential stability of discrete-time bidirectional associative m...
In this paper, a generalized model of bi-directional associative memory (BAM) neural networks delays...
This paper deals with the problem of robust stability of the class of bidirectional associative memo...
In this paper, the robust stability problem is investigated for a class of bidirectional associative...
AbstractA bidirectional associative memory neural network model with distributed delays is considere...
Impulsive bidirectional associative memory neural network model with time-varying delays and reactio...
In this paper, we consider the problem on exponential stability analysis of the stochastic impulsive...
This paper presents an easily verifiable delay independent sufficient condition for the global robus...
AbstractSome sufficient conditions are obtained for the existence and global exponential stability o...
AbstractUsing M-matrix and topological degree tool, sufficient conditions are obtained for the exist...
This paper presents a sufficient condition for the existence, uniqueness and global asymptotic stabi...
This paper presents some new sufficient conditions for the global robust asymptotic stability of the...
In this paper, a class of generalized bi-directional associative memory (BAM) neural networks with m...