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Deploying the sensor nodes at the best locations for random field reconstruction via sensor network is a fundamental task. One-dimensional random field is a stochastic process. In this paper, we first propose an optimal sensor deployment strategy for Wiener process estimation. The optimal locations for the deployed sensors are uniformly distributed in the field. In addition, we propose a suboptimal...
This paper presents a distributed EM algorithm for Gaussian mixtures based on diffusion scheme over random sensor networks. In the E-step of this method, sensor nodes compute the local statistics by using local observation data and parameters estimated at last iterative step. A diffusion step is implemented over the time-varying communication networks after E-step. In this step, the communication...
This paper considers stabilization of network controlled systems (NCSs) with multiple-packet transmission. For NCSs node devices acting over a limited communication channel, we are particularly interested in the case that only one packet containing part of the state information can be transmitted at a time. Even if a state feedback is intended for the original system, control such a system is an output...
This paper is concerned with the estimation problem for discrete-time stochastic linear systems with multiple packet dropouts. Based on a recently developed model for multiple-packet dropouts, the original system is transferred to a stochastic parameter system by augmentation of the state and measurement. The optimal full-order linear filter of the form of employing the received outputs at the current...
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