Abstract
This paper considers the finite time state estimation problem of complex-valued bidirectional associative memory (BAM) neutral-type neural networks with time-varying delays. By resorting to the Lyapunov function approach, the Wirtinger inequality and the reciprocally convex approach, a delay-dependent criterion in terms of LMIs is established to guarantee the finite-time boundedness of the error-state system for the addressed system. Meanwhile, an effective state estimator is designed to estimate the network states through the available output measurements. Finally, a numerical example is presented to demonstrate the effectiveness of the proposed results.
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