Results 281 to 290 of about 2,518,110 (330)

Minimum f-Divergence Estimation With Applications to Degradation Data Analysis

IEEE Transactions on Information Theory, 2022
Minimizing the divergence between two probability distributions offers an alternative parameter estimation method. The current literature mainly focuses on minimizing the Kullback-Leibler (K-L) divergence between the true and the proposed models in which
Fodé Zhang, Keung Tony Ng
exaly   +2 more sources

A Watermarking Strategy Against Linear Deception Attacks on Remote State Estimation Under K–L Divergence

IEEE Transactions on Industrial Informatics, 2021
In this article, a defense method with watermarking to detect linear deception attack under Kullback–Leibler (K–L) divergence detector in cyber–physical system (CPS) is proposed.
Di Wang, Jiahao Huang, Yang Tang
exaly   +2 more sources

Worst-Case Stealthy Innovation-Based Linear Attacks on Remote State Estimation Under Kullback–Leibler Divergence

IEEE Transactions on Automatic Control, 2022
With the wide application of cyber-physical systems, stealthy attacks on remote state estimation have attracted increasing research attention. Recently, various stealthy innovation-based linear attack models were proposed, in which the relaxed ...
Jun Shang, Hao Yu, Tongwen Chen
semanticscholar   +1 more source

Calibrated Tree Priors for Relaxed Phylogenetics and Divergence Time Estimation

Systematic Biology, 2012
The use of fossil evidence to calibrate divergence time estimation has a long history. More recently, Bayesian Markov chain Monte Carlo has become the dominant method of divergence time estimation, and fossil evidence has been reinterpreted as the ...
Joseph Heled, Alexei J Drummond, Drummond Alexei J   +2 more
exaly   +2 more sources

On the Estimation of alpha-Divergences [PDF]

, 2018
We propose new nonparametric, consistent Renyi-alpha and Tsallis-alpha divergence estimators for continuous distributions. Given two independent and identically distributed samples, a `brute force' approach would be simply to estimate the underlying densities, and plug these densities into the corresponding formulas.
Barnabás Póczos, Jeff G. Schneider
openaire   +1 more source

Functional Bregman Divergence and Bayesian Estimation of Distributions

IEEE Transactions on Information Theory, 2008
A class of distortions termed functional Bregman divergences is defined, which includes squared error and relative entropy. A functional Bregman divergence acts on functions or distributions, and generalizes the standard Bregman divergence for vectors ...
Maya R Gupta
exaly   +1 more source

The estimation of genetic divergence

Journal of Molecular Evolution, 1981
We have independently repeated the computer simulations on which Nei and Tateno (1978) base their criticism of REH theory and have extended the analysis to include mRNAs as well as proteins. The simulation data confirm the correctness of the REH method. The high average value of the fixation intensity mu 2 found by Nei and Tateno is due to two factors:
R, Holmquist, T, Conroy
openaire   +2 more sources

Bearing degradation assessment and remaining useful life estimation based on Kullback-Leibler divergence and Gaussian processes regression

, 2021
Accurate monitoring of degradation in bearing is essential for preventing unexpected shutdown of a machinery system. This paper proposes a novel health degradation indicator for machineries, based on a Kullback-Leibler divergence.
P. Kumar, L. Kumaraswamidhas, S. K. Laha
semanticscholar   +1 more source

Nonparametric Estimation of Küllback-Leibler Divergence

Neural Computation, 2014
In this letter, we introduce an estimator of Küllback-Leibler divergence based on two independent samples. We show that on any finite alphabet, this estimator has an exponentially decaying bias and that it is consistent and asymptotically normal. To explain the importance of this estimator, we provide a thorough analysis of the more standard plug-in ...
Zhiyi Zhang 0003, Michael Grabchak
openaire   +2 more sources