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008181129s2018 ||| | | | eng d
020 ▼a 9780438353770
035 ▼a (MiAaPQ)AAI10843251
035 ▼a (MiAaPQ)umn:19489
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0491 ▼f DP
0820 ▼a 621.3
1001 ▼a Najafi, M. Hassan.
24510 ▼a New Views for Stochastic Computing: From Time-encoding to Deterministic Processing.
260 ▼a [S.l.] : ▼b University of Minnesota., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 169 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
500 ▼a Adviser: David J. Lilja.
5021 ▼a Thesis (Ph.D.)--University of Minnesota, 2018.
520 ▼a Stochastic computing (SC), a paradigm first introduced in the 1960s, has received considerable attention in recent years as a potential paradigm for emerging technologies and ''post-CMOS'' computing. Logical computation is performed on random bi
520 ▼a This dissertation begins by proposing a highly unorthodox idea: performing computation with digital constructs on time-encoded analog signals. We introduce a new, energy-efficient, high-performance, and much less costly approach for SC using tim
520 ▼a Poor progressive precision is the main challenge with the recently developed deterministic methods of SC. We propose a high-quality down-sampling method which significantly improves the processing time and the energy consumption of these determi
590 ▼a School code: 0130.
650 4 ▼a Electrical engineering.
650 4 ▼a Computer engineering.
690 ▼a 0544
690 ▼a 0464
71020 ▼a University of Minnesota. ▼b Electrical/Computer Engineering.
7730 ▼t Dissertation Abstracts International ▼g 80-01B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0130
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T14999913 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자 ▼b 관리자