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Reduced Order Models and Approximations for Hardware Acceleration of Neural Networks.
Reduced Order Models and Approximations for Hardware Acceleration of Neural Networks.
- 자료유형
- 학위논문
- Control Number
- 0016053667
- International Standard Book Number
- 9798535548562
- Dewey Decimal Classification Number
- 621.3
- Main Entry-Personal Name
- Azari, Elham.
- Publication, Distribution, etc. (Imprint
- [S.l.] : Arizona State University., 2021
- Publication, Distribution, etc. (Imprint
- Ann Arbor : ProQuest Dissertations & Theses, 2021
- Physical Description
- 171 p.
- General Note
- Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
- General Note
- Advisor: Vrudhula, Sarma.
- Dissertation Note
- Thesis (Ph.D.)--Arizona State University, 2021.
- Restrictions on Access Note
- This item must not be sold to any third party vendors.
- Subject Added Entry-Topical Term
- Computer engineering.
- Subject Added Entry-Topical Term
- Computer science.
- Subject Added Entry-Topical Term
- Design.
- Subject Added Entry-Topical Term
- Energy efficiency.
- Subject Added Entry-Topical Term
- Accuracy.
- Subject Added Entry-Topical Term
- Random variables.
- Subject Added Entry-Topical Term
- Sensitivity analysis.
- Subject Added Entry-Topical Term
- Classification.
- Index Term-Uncontrolled
- Hardware acceleration
- Index Term-Uncontrolled
- LSTM
- Index Term-Uncontrolled
- Machine learning
- Index Term-Uncontrolled
- Neural networks
- Index Term-Uncontrolled
- Polynomial chaos
- Index Term-Uncontrolled
- Uncertainty quantification
- Added Entry-Corporate Name
- Arizona State University Computer Engineering
- Host Item Entry
- Dissertations Abstracts International. 83-02B.
- Host Item Entry
- Dissertation Abstract International
- Electronic Location and Access
- 로그인을 한후 보실 수 있는 자료입니다.
- Control Number
- joongbu:608961
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