TY - JOUR
T1 - Exponential-weighting-basedmaximum likelihood for determining measurement random latency probability in network systems
AU - Wang, Xiaoxu
AU - Pan, Quan
PY - 2016/12
Y1 - 2016/12
N2 - 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.
AB - 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.
KW - Exponential Weighting
KW - Filter
KW - Maximum Multi-Step Likelihood
KW - Nonlinear Parameter Determination
UR - http://www.scopus.com/inward/record.url?scp=85007039314&partnerID=8YFLogxK
U2 - 10.20965/jaciii.2016.p1060
DO - 10.20965/jaciii.2016.p1060
M3 - 文章
AN - SCOPUS:85007039314
SN - 1343-0130
VL - 20
SP - 1060
EP - 1064
JO - Journal of Advanced Computational Intelligence and Intelligent Informatics
JF - Journal of Advanced Computational Intelligence and Intelligent Informatics
IS - 7
ER -