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This paper is concerned with the problem of state estimation for a class of discrete-time chaotic systems with or without time delays. A unified model consisting of a linear dynamic system and a bounded static nonlinear operator is employed to describe these systems, such as chaotic neural networks, Chua's circuits, Hénon map, etc. Based on the H∞(More)
In order to increase the localization coverage while keeping the localization error small in a unique network architecture in which there are not evenly distributed anchor nodes with great ability of communication or additional infrastructure, a Top-down Positioning Scheme (TPS) for underwater acoustic sensor networks is proposed. By defining node’s(More)
This brief studies exponential H(infinity) synchronization of a class of general discrete-time chaotic neural networks with external disturbance. On the basis of the drive-response concept and H(infinity) control theory, and using Lyapunov-Krasovskii (or Lyapunov) functional, state feedback controllers are established to not only guarantee exponential(More)
— With the advance of semiconductor, multi-core architecture is inevitable in today's embedded system design. Nested loops are usually the most critical part in multimedia and high performance DSP (Digital Signal Processing) systems. Hence, maximizing loop parallelism is an important issue to improve the performance of a modern compiler. This paper studies(More)
A unified neural network model termed standard neural network model (SNNM) is advanced. Based on the robust L(2) gain (i.e. robust H(infinity) performance) analysis of the SNNM with external disturbances, a state-feedback control law is designed for the SNNM to stabilize the closed-loop system and eliminate the effect of external disturbances. The control(More)
This paper presents an exponential synchronization scheme between two chaotic systems with different structures and parameters. A unified model consisting of a linear dynamic system and a bounded static nonlinear operator is employed to describe these totally different chaotic systems. A novel state feedback control law is established to exponentially(More)
This brief proposes an output tracking control for a class of discrete-time nonlinear systems with disturbances. A standard neural network model is used to represent discrete-time nonlinear systems whose nonlinearity satisfies the sector conditions. H∞ control performance for the closed-loop system including the standard neural network model, the reference(More)