Stationary Random Processes
Stationary Random Processes is a stochastic process in which the statistical properties such as the mean, variance, and autocorrelation remain constant over time, distinguishing it from non-stationary random processes by exhibiting time-invariant probabilistic behavior.
1.9K
Publications
181.8K
Citations
2.5K
Authors
983
Institutions
Publications per year
2017–2026
133
Parents
1.9K
Probability, Random Variables, and Stochastic Processes
Irwin Miller, Anthanasios Papoulis · Technometrics · 1966 · 6.5K citations
Engineering, Mathematics, Physics +14
High-resolution frequency-wavenumber spectrum analysis
J. Capon · Proceedings of the IEEE · 1969 · 6.2K citations
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University of North Carolina at Chapel Hill, United States
10 publications · 2.4K citations
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983
University of California San Diego
San Diego, United States
23 h-index
50 publications
3.1K citations
Massachusetts Institute of Technology
Cambridge, United States
19 h-index
42 publications
9K citations
Stanford University
Stanford, United States
18 h-index
30 publications
2.1K citations

Centre National de la Recherche Scientifique
Paris, France
17 h-index
47 publications
1.3K citations

Cornell University
Ithaca, United States
16 h-index
32 publications
1K citations

Australian National University
Canberra, Australia
16 h-index
21 publications
840 citations

University of Manchester
Manchester, United Kingdom
15 h-index
29 publications
2.2K citations
University of California, Berkeley
Berkeley, United States
15 h-index
22 publications
889 citations
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85 publications · 5.1K citations
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JAP · 74 publications · 4.6K citations
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60 publications · 2.1K citations
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38 publications · 5.6K citations
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54 publications · 4K citations
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