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P. P. Vaidyanathan
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Name: Caroline M. Murphy
Email: [email protected]
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Home  /  People  /  P. P. Vaidyanathan

P. P. Vaidyanathan

Kiyo and Eiko Tomiyasu Professor of Electrical Engineering
B.Sc., University of Calcutta, 1974; B.Tech., 1977; M.Tech., 1979; Ph.D., University of California, Santa Barbara, 1982. Assistant Professor, Caltech, 1983-88; Associate Professor, 1988-93; Professor, 1993-2018; Tomiyasu Professor, 2018-; Executive Officer, 2002-05.
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Research interests: current emphasis is on sparse sampling in one and multiple dimensions, network signal processing, number theoretic signal processing, and applications in digital communications, array processing, radar signal processing, genomic signal processing, and multirate systems and filter banks.

Overview

Theoretical and computer-oriented work on a wide variety of problems in digital signal processing. Sparse sensor arrays, sparse signal reconstruction, compressive sensing, array signal processing, multirate digital filters and filter banks, radar signal processing, genomic signal processing, number theoretical signal processing, spectrum sensing, and graph signal processing.

Related News

P.P. Vaidyanathan Receives IEEE Jack S. Kilby Signal Processing Medal
Vaidyanathan's student Pranav Kulkarni Receives Best Paper Award
Vaidyanathan and Liu Receive Best Paper Award
P.P. Vaidyanathan Elected to Indian National Academy of Engineering
P. P. Vaidyanathan Receives Athanasios Papoulis Award
Srikanth Venkata Tenneti Wins Charles Wilts Prize
Professor Vaidyanathan Elected to the National Academy of Engineering
Meet the 2017 Amazon Fellows
Professor Vaidyanathan Receives IEEE Signal Processing Society's Highest Award
Graduate Student Wins Best Paper Prize
Read more news   >

Publications

View more publications on feeds.library.caltech.edu

Related Courses

2022-23
EE 1 – The Science of Data, Signals, and Information
EE 111 – Signal-Processing Systems and Transforms
2021-22
EE 111 – Signal-Processing Systems and Transforms
EE 112 – Introduction to Signal Processing from Data
2020-21
EE 1 – The Science of Data, Signals, and Information
EE 111 – Signal-Processing Systems and Transforms
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