22 May 2014 Improving the efficiency of nonparametric entropy estimation
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Abstract
A problem of improving the efficiency of nonparametric entropy estimation for discrete stationary ergodic processes is considered. The estimation depends on selection of underlying metric on the space of right-sided infinite sequences. Proposed is a new family of metrics which depend on a set of parameters. The estimator is linearly dependent on the parameters, and the best accuracy is achieved by solution of a system of linear equations.
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Evgeniy A. Timofeev, Alexei Kaltchenko, "Improving the efficiency of nonparametric entropy estimation", Proc. SPIE 9118, Independent Component Analyses, Compressive Sampling, Wavelets, Neural Net, Biosystems, and Nanoengineering XII, 911818 (22 May 2014); doi: 10.1117/12.2049575; https://doi.org/10.1117/12.2049575
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