Signal Processing Acceleration
Signal Processing Acceleration is a hardware acceleration technique that specifically optimizes the execution of signal processing algorithms by leveraging specialized computational architectures to achieve superior performance, efficiency, or throughput compared to general-purpose processors.
144
Publications
12.5K
Citations
2.6K
Authors
425
Institutions
Publications per year
2017–2026
36
Parents
144
FFTW: an adaptive software architecture for the FFT
Matteo Frigo, Steven G. Johnson · 2002 · 1.8K citations
Time Series FeatuRe Extraction on basis of Scalable Hypothesis tests (tsfresh – A Python package)
Maximilian Christ, N. Braun, Julius Neuffer et al. · Neurocomputing · 2018 · 1.2K citations · Full text
Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields
Jonathan T. Barron, Ben Mildenhall, Dor Verbin et al. · 2023 · 451 citations
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425
Georgia Institute of Technology
Atlanta, United States
5 h-index
13 publications
983 citations
The University of Texas at Austin
Austin, United States
5 h-index
17 publications
1.1K citations
Tsinghua University
Beijing, China
4 h-index
11 publications
457 citations
Hewlett-Packard (United States)
Palo Alto, United States
4 h-index
6 publications
285 citations
Intel (United States)
Santa Clara, United States
3 h-index
4 publications
126 citations

University of Freiburg
Freiburg im Breisgau, Germany
3 h-index
27 publications
1.7K citations
Texas Instruments (United States)
Dallas, United States
3 h-index
49 publications
927 citations
Massachusetts Institute of Technology
Cambridge, United States
3 h-index
6 publications
3.9K citations
1–8 of 425
Repository · 4 publications · 63 citations
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3 publications · 54 citations
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3 publications · 1.9K citations
3
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3 publications · 114 citations
3
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3 publications · 493 citations
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