Exponential-weighting-basedmaximum likelihood for determining measurement random latency probability in network systems

科研成果: 期刊稿件文章同行评审

摘要

The standard nonlinear Gaussian approximation (GA) filter used for randomly delayed measurement in network systems, usually assume that the measurement random latency probability (MRLP) is known a priori. However, practically, the MRLP may be unknown or even be time-varying, causing the standard nonlinear GA filter to certainly fail. Motivated by the above situation, this paper is concerned with the application of maximum likelihood based on exponential weighting for adaptively determining the MRLP. Furthermore, an adaptive version of the nonlinear GA filter is proposed for joint state estimation and MRLP determination. Finally, simulation results demonstrate the performance of the new adaptive GA filter compared with the standard one.

源语言英语
页(从-至)1060-1064
页数5
期刊Journal of Advanced Computational Intelligence and Intelligent Informatics
20
7
DOI
出版状态已出版 - 12月 2016

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