A NONLINEAR SUBSPACE APPROACH FOR PARAMETRIC ESTIMATION OF PDFS FROM SHORT DATA RECORDS WITH APPLICATION TO RAYLEIGH FADING

A Nonlinear Subspace Approach for Parametric Estimation of PDFs From Short Data Records With Application to Rayleigh Fading

This paper tackles the issue of real-time parametric estimation of a wide class of probability density functions from limited datasets.This type of estimation addresses recent applications that require joint sensing Books and actuation.The suggested estimator operates in the nonlinear subspace that the parameter space of the distribution creates in

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Embodied Heuristics

Intelligence evolved to cope with situations of uncertainty generated by nature, predators, and the behavior of conspecifics.To this end, humans and other animals acquired special abilities, including heuristics that allow for swift action in face of scarce information.In this article, I introduce the concept of embodied heuristics, that is, innate

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