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Abstract
For neural networks with constant or time-varying delays, the problems of determining
the exponential stability and estimating the exponential convergence rate are studied
in this paper. An approach combining the Lyapunov-Krasovskii functionals with the
linear matrix inequality is taken to investigate the problems, which provide bounds
on the interconnection matrix and the activation functions, so as to guarantee the
systems' exponential stability. Some criteria for the exponentially stability, which
give information on the delay-dependence property, are derived. The results obtained
in this paper provide one more set of easily verified guidelines for determining the
exponentially stability of delayed neural networks, which are less conservative and
less restrictive than the ones reported so far in the literature.