Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/49116
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dc.titleTuning an underwater communication link
dc.contributor.authorSATISH SHANKAR
dc.date.accessioned2014-01-31T18:00:29Z
dc.date.available2014-01-31T18:00:29Z
dc.date.issued2013-05-07
dc.identifier.citationSATISH SHANKAR (2013-05-07). Tuning an underwater communication link. ScholarBank@NUS Repository.
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/49116
dc.description.abstractA family of machine learning algorithms to optimize an underwater communication link are developed in this thesis. We continuously adjust the physical layer parameters of a point-to-point communication link and aim to maximize the average data rate. The algorithms are statistical in nature and are driven by bit error rate information, hence they are independent of the actual physical layer implementation.
dc.language.isoen
dc.subjectunderwater communication, machine learning, reinforcement learning, signal processing, adaptive modulation, multi-armed bandits, bandit learning
dc.typeThesis
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.contributor.supervisorMANDAR ANIL CHITRE
dc.description.degreeMaster's
dc.description.degreeconferredMASTER OF ENGINEERING
dc.identifier.isiutNOT_IN_WOS
Appears in Collections:Master's Theses (Open)

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