Algorithmic Power Minimization
Algorithmic Power Minimization is a computational optimization strategy that reduces dynamic power consumption in digital systems by modifying algorithmic structures or data flow to minimize switching activity and operational complexity at the architectural level.
44
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1.6K
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134
Authors
60
Institutions
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2017–2026
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Algorithmic problems in power management
Sandy Irani, Kirk Pruhs · ACM SIGACT News · 2005 · 296 citations
Deep Spiking Neural Networks for Large Vocabulary Automatic Speech Recognition
Jibin Wu, Emre Yılmaz, Malu Zhang et al. · Frontiers in Neuroscience · 2020 · 130 citations · Full text
Ilhem Boussaïd, Amitava Chatterjee, Patrick Siarry et al. · IEEE Transactions on Vehicular Technology · 2011 · 75 citations
Resource Allocation for Power-Efficient IRS-Assisted UAV Communications
Yuanxin Cai, Zhiqiang Wei, Shaokang Hu et al. · 2020 · 69 citations
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École Polytechnique Fédérale de Lausanne
Lausanne, Switzerland
3 h-index
5 publications
158 citations
University of California, Santa Barbara
Santa Barbara, United States
3 h-index
6 publications
256 citations
University of California San Diego
San Diego, United States
3 h-index
6 publications
240 citations
Technical University of Munich
Munich, Germany
2 h-index
5 publications
94 citations
University of South Florida
Tampa, United States
2 h-index
5 publications
157 citations

Edinburgh Napier University
Edinburgh, United Kingdom
2 h-index
4 publications
148 citations
National Tsing Hua University
Hsinchu, Taiwan
2 h-index
6 publications
103 citations
Stanford University
Stanford, United States
2 h-index
5 publications
116 citations
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1 publications · 14 citations
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Conference · 1 publications · 48 citations
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Conference · 1 publications · 19 citations
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