NDLI: Approximate optimal estimation based on Kullback–Leibler divergence for lossy networks without acknowledgement

Content Provider	IET Digital Library
Author	Liang, Shi Qiu, Chan Liu, Zhenyu Peng, Xiang Liu, Daxin Tan, Jianrong
Abstract	This study is concerned with the estimation problem for systems with both missing inputs and measurements but without any acknowledgement mechanism. The acknowledgement mechanism is used to provide the estimator with the status information that whether the input is lost or not during the transmission. Affected by the missing input with unknown status information, the probability density function of system state is a Gaussian mixture, of which the number of terms is growing exponentially with time. Two major limitations of state estimation for these systems are (i) the computational inefficiency of the optimal estimation and (ii) the undetermined stability of the approximate optimal estimation. Thus, the aim of this study is to design an estimator such that it can enhance computational efficiency greatly while its stability can be guaranteed simultaneously. Using Kullback–Leiber divergence, an approximate optimal estimator, which is named as the KLD estimator, is developed as an efficient alternative to the optimal one. By establishing a Riccati-like equation subject to both-side packet dropouts, a sufficient and necessary condition is given for the stability of the KLD estimator. It reveals an interesting fact that the proposed approximate optimal estimator has the same stability as the optimal estimator.
Starting Page	1804
Ending Page	1813
Page Count	10
ISSN	17518644
Volume Number	13
e-ISSN	17518652
Issue Number	Issue 12, Aug (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cta/13/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cta.2018.6302
Journal	IET Control Theory & Applications
Publisher Date	2019-05-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Approximate Optimal Estimation Approximate Optimal Estimator Approximation Theory Both-side Packet Dropouts Communication System Theory Data Communication Estimation Problem Estimation Theory Gaussian Mixture Gaussian Processes Interpolation And Function Approximation KLD Estimator Kullback-Leiber Divergence Lossy Network Mixture Model Numerical Analysis Probability Riccati-like Equation State Estimation Statistics
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Control and Systems Engineering Human-Computer Interaction Electrical and Electronic Engineering Computer Science Applications

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