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020 ▼a 9780438139817
035 ▼a (MiAaPQ)AAI10689093
035 ▼a (MiAaPQ)umd:18711
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0491 ▼f DP
0820 ▼a 620
1001 ▼a Boda, Vinay Praneeth.
24510 ▼a Sampling Rate Distortion.
260 ▼a [S.l.] : ▼b University of Maryland, College Park., ▼c 2017
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2017
300 ▼a 172 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
500 ▼a Adviser: Prakash Narayan.
5021 ▼a Thesis (Ph.D.)--University of Maryland, College Park, 2017.
520 ▼a Consider a memoryless multiple source with m components of which a (possibly randomized) subset of k &le
520 ▼a We begin with a discrete memoryless multiple source whose joint probability mass function (pmf) is taken to be known. A notion of sampling rate distortion function is introduced to study the mentioned tradeoffs, and is characterized first for f
520 ▼a Building on this, we consider a universal setting where the joint pmf of a discrete memoryless multiple source is known only to belong to a finite family of pmfs. In Bayesian and nonBayesian settings, single-letter characterizations are provide
520 ▼a Lastly, we consider a jointly Gaussian multiple memoryless source, to be reconstructed under a mean-squared error distortion criterion, with joint probability distribution function known only to belong to an uncountable family of probability de
520 ▼a The questions addressed in this dissertation are motivated by various applications, e.g., dynamic thermal management for multicore processors, in-network computation and satellite imaging.
590 ▼a School code: 0117.
650 4 ▼a Engineering.
690 ▼a 0537
71020 ▼a University of Maryland, College Park. ▼b Electrical Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-11B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0117
791 ▼a Ph.D.
792 ▼a 2017
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14996773 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자 ▼b 관리자