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" ADAPTIVE SENSING IN UNCERTAIN ENVIRONMENTS: MAXIMUM LIKELIHOOD, SENSOR NETWORKS, AND REINFORCEMENT LEARNING "


Document Type : Latin Dissertation
Language of Document : English
Record Number : 149329
Doc. No : ET21121
Main Entry : Doron Blatt
Title Proper : ADAPTIVE SENSING IN UNCERTAIN ENVIRONMENTS: MAXIMUM LIKELIHOOD, SENSOR NETWORKS, AND REINFORCEMENT LEARNING
Note : This document is digital این مدرک بصورت الکترونیکی می باشد
Abstract : The advent of distributed and agile sensing systems that collect data in multiplelocations and through a variety of sensing modalities has brought about new andexciting challenges to the field of signal processing. Motivated by problems thatarise in the development of these systems, the thesis makes contributions in threedomains: (1) distributed optimization for inference in sensor networks, (2) statisticaltests for optimality that mitigate the problem of sensitivity to local maxima, and (3)development and analysis of reinforcement learning solutions to stochastic decisionproblems for resource allocation in agile sensing.A novel incremental gradient.
Subject : Electericl tess
: برق
electronic file name : TL44269.pdf
Title and statement of responsibility and : ADAPTIVE SENSING IN UNCERTAIN ENVIRONMENTS: MAXIMUM LIKELIHOOD, SENSOR NETWORKS, AND REINFORCEMENT LEARNING [Thesis]
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TL44269.pdf
TL44269.pdf
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