Adaptive Signal Processing
Adaptive Signal Processing is a signal processing paradigm that dynamically modifies its parameters or structure in response to changes in input signal characteristics, distinguishing it from static or fixed signal processing methods through its capacity for real-time self-optimization based on ongoing performance evaluation.
2.2K
Publications
141.8K
Citations
4K
Authors
1.2K
Institutions
Publications per year
2017–2026
261
Parents
2.2K
Adaptive noise cancelling: Principles and applications
Bernard Widrow, John R. Glover, J. McCool et al. · Proceedings of the IEEE · 1975 · 3.9K citations
Neuromorphic electronic systems
Carver Mead · Proceedings of the IEEE · 1990 · 2.3K citations
Engineering, Computer Engineering, Electrical Engineering +10
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Stanford University
Stanford, United States
29 h-index
84 publications
39.8K citations

Southwest Jiaotong University
Chengdu, China
25 h-index
89 publications
3.4K citations
MIT Lincoln Laboratory
Lexington, United States
24 h-index
55 publications
5.3K citations
Massachusetts Institute of Technology
Cambridge, United States
22 h-index
47 publications
4.2K citations

Imperial College London
London, United Kingdom
19 h-index
65 publications
3K citations

United States Air Force Research Laboratory
Wright-Patterson AFB, United States
19 h-index
37 publications
1.8K citations
University of Utah
Salt Lake City, United States
18 h-index
35 publications
2.1K citations
University of California, Santa Barbara
Santa Barbara, United States
18 h-index
37 publications
2.9K citations
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265 publications · 25.4K citations
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94 publications · 11.4K citations
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51 publications · 3.1K citations
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59 publications · 3.5K citations
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49 publications · 6.9K citations
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