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Engineering Recurrent Neural Networks for Low-Rank and Noise-Robust Computation
Engineering Recurrent Neural Networks for Low-Rank and Noise-Robust Computation
상세정보
- 자료유형
- 학위논문파일 국외
- ISBN
- 9798505571996
- DDC
- 620
- 서명/저자
- Engineering Recurrent Neural Networks for Low-Rank and Noise-Robust Computation
- 발행사항
- [Sl] : Stanford University, 2021
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2021
- 형태사항
- 71 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
- 주기사항
- Advisor: Ganguli, Surya;Baccus, Stephen;Druckmann, Shaul;Newsome, William;Sussillo, David.
- 학위논문주기
- Thesis (Ph.D.)--Stanford University, 2021.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 일반주제명
- Construction
- 일반주제명
- Neurons
- 일반주제명
- Memory
- 일반주제명
- Signal processing
- 일반주제명
- Neural networks
- 일반주제명
- Equilibrium
- 일반주제명
- Phase transitions
- 일반주제명
- Approximation
- 일반주제명
- Neurosciences
- 일반주제명
- Connectivity
- 일반주제명
- Engineering
- 일반주제명
- Noise
- 일반주제명
- Dynamical systems
- 일반주제명
- Artificial intelligence
- 일반주제명
- Civil engineering
- 일반주제명
- Mathematics
- 일반주제명
- Acoustics
- 기타저자
- Stanford University.
- 기본자료저록
- Dissertations Abstracts International. 83-02B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008220131s2021 us c eng d■020 ▼a9798505571996
■035 ▼a(MiAaPQ)AAI28483323
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a620
■1001 ▼aStock, Christopher Hopkins.
■24510▼aEngineering Recurrent Neural Networks for Low-Rank and Noise-Robust Computation
■260 ▼a[Sl]▼bStanford University▼c2021
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2021
■300 ▼a71 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 83-02, Section: B.
■500 ▼aAdvisor: Ganguli, Surya;Baccus, Stephen;Druckmann, Shaul;Newsome, William;Sussillo, David.
■5021 ▼aThesis (Ph.D.)--Stanford University, 2021.
■506 ▼aThis item must not be sold to any third party vendors.
■590 ▼aSchool code: 0212.
■650 4▼aConstruction
■650 4▼aNeurons
■650 4▼aMemory
■650 4▼aSignal processing
■650 4▼aNeural networks
■650 4▼aEquilibrium
■650 4▼aPhase transitions
■650 4▼aApproximation
■650 4▼aNeurosciences
■650 4▼aConnectivity
■650 4▼aEngineering
■650 4▼aNoise
■650 4▼aDynamical systems
■650 4▼aArtificial intelligence
■650 4▼aCivil engineering
■650 4▼aMathematics
■650 4▼aAcoustics
■690 ▼a0986
■690 ▼a0800
■690 ▼a0543
■690 ▼a0537
■690 ▼a0405
■690 ▼a0317
■71020▼aStanford University.
■7730 ▼tDissertations Abstracts International▼g83-02B.
■773 ▼tDissertation Abstract International
■790 ▼a0212
■791 ▼aPh.D.
■792 ▼a2021
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16051772▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202202▼f2022
