Author Description

<p>This book presents the novel state estimation methods for several classes of networked multi-rate systems including state estimation methods for networked multi-rate systems with various complex networked-induced phenomena and communication protocols. The systems investigated include the stochastic nonlinear systems, the time-delay systems, the linear repetitive processes, and the artificial neural networks. The techniques used are mainly the Lyapunov stability theory, the optimal estimation theory, the lifting technique, and certain convex optimization method.</p><p>Features-</p><p>-Gives a systematic investigation of the state estimation of multi-rate systems </p><p>-Discusses results on state estimation problems under network-induced complexities </p><p>- Studies different kinds of multi-rate systems including multi-rate nonlinear systems, multi-rate neural networks, and multi-rate linear repetitive processes </p><p>-Explores network-enhanced complexities and communication protocols </p><p>- Includes case studies to show the applicability of the developed estimation algorithms including practical examples like DC servo system and continuous stirred tank reactor system </p><p>This book is aimed at graduate students and researchers in signal processing, control systems, and electrical engineering.</p>