Journal
NEURAL COMPUTING & APPLICATIONS
Volume 20, Issue 3, Pages 451-460Publisher
SPRINGER LONDON LTD
DOI: 10.1007/s00521-010-0415-3
Keywords
Neutral BAM neural networks; Mixed time-delays; Delay decomposition; Exponential stability; Linear matrix inequalities (LMIs)
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Funding
- National Science Foundation of China [60974017]
- Specialized Research Fund for the Doctoral Program of High Education, China [200803370002]
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This paper is concerned with the exponential stability analysis problem for a class of neutral bidirectional associative memory neural networks with mixed time-delays, where discrete, distributed and neutral delays are involved. By utilizing the delay decomposition approach and an appropriately constructed Lyapunov-Krasovskii functional, some novel delay-dependent and decay rate-dependent criteria for the exponential stability of the considered neural networks are derived and presented in terms of linear matrix inequalities. Furthermore, the maximum allowable decay rate can be estimated based on the obtained results. Three numerical examples are given to demonstrate the effectiveness of the proposed method.
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