Global robust asymptotic stability analysis of uncertain switched Hopfield neural networks with time delay in the leakage term
 P. Balasubramaniam,
 V. Vembarasan,
 R. Rakkiyappan
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This paper deals with the problem of delaydependent global robust asymptotic stability of uncertain switched Hopfield neural networks (USHNNs) with discrete interval and distributed timevarying delays and time delay in the leakage term. Some Lyapunov––Krasovskii functionals are constructed and the linear matrix inequality (LMI) approach are employed to derive some delaydependent global robust stability criteria which guarantee the global robust asymptotic stability of the equilibrium point for all admissible parametric uncertainties. The proposed results that do not require the boundedness, differentiability, and monotonicity of the activation functions. Moreover, the stability behavior of USHNNs is very sensitive to the time delay in the leakage term. It can be easily checked via the LMI control toolbox in Matlab. In the absence of leakage delay, the results obtained are also new results. Finally, nine numerical examples are given to show the effectiveness of the proposed results.
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 Title
 Global robust asymptotic stability analysis of uncertain switched Hopfield neural networks with time delay in the leakage term
 Journal

Neural Computing and Applications
Volume 21, Issue 7 , pp 15931616
 Cover Date
 20121001
 DOI
 10.1007/s005210110639x
 Print ISSN
 09410643
 Online ISSN
 14333058
 Publisher
 SpringerVerlag
 Additional Links
 Topics
 Keywords

 Switched systems
 Hopfield neural networks
 Linear matrix inequality
 Mixed interval timevarying delay
 Leakage delay
 Industry Sectors
 Authors

 P. Balasubramaniam ^{(1)}
 V. Vembarasan ^{(1)}
 R. Rakkiyappan ^{(2)}
 Author Affiliations

 1. Department of Mathematics, Gandhigram Rural University, Gandhigram, Tamilnadu, India
 2. Department of Mathematics, Bharathiyar University, Coimbatore, Tamilnadu, India