Authors:
- Shows how statistical signal processing helps in the analysis of random signals
- Discusses the frequency estimation problem
- Is useful for senior undergraduate and graduate students specializing in mathematics or statistics
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Table of contents (11 chapters)
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Front Matter
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Back Matter
About this book
Authors and Affiliations
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Theoretical Stat and Mathematics Unit, Indian Statistical Institute, New Delhi, India
Swagata Nandi
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Department of Mathematics and Statistics, Indian Institute of Technology Kanpur, Kanpur, India
Debasis Kundu
About the authors
Swagata Nandi is currently an Associate Professor at the Theoretical Statistics and Mathematics Unit of the Indian Statistical Institute, Delhi Center. She received her M.Sc. and Ph.D. from the Indian Institute of Technology, Kanpur. In her Ph. D, she worked under the guidance of Professor Debasis Kundu and Professor S. K. Iyer. Before joining Indian Statistical Institute in 2005, she was a Postdoctoral Fellow at the University of Heidelberg and at the University of Mannheim, Germany. Her research interests include statistical signal processing, nonlinear regression, analysis of surrogate data, EM algorithms and survival analysis. She has published more than 35 research papers in various national and international journals and co-authored a monograph on Statistical Signal Processing. She is the recipient of the Indian Science Congress Association Young Scientist award and the C.L. Chandana Award for Students.
Bibliographic Information
Book Title: Statistical Signal Processing
Book Subtitle: Frequency Estimation
Authors: Swagata Nandi, Debasis Kundu
DOI: https://doi.org/10.1007/978-981-15-6280-8
Publisher: Springer Singapore
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Singapore Pte Ltd. 2020
Hardcover ISBN: 978-981-15-6279-2Published: 22 August 2020
Softcover ISBN: 978-981-15-6282-2Published: 22 August 2021
eBook ISBN: 978-981-15-6280-8Published: 21 August 2020
Edition Number: 2
Number of Pages: XXIII, 265
Number of Illustrations: 31 b/w illustrations, 22 illustrations in colour
Topics: Statistics and Computing/Statistics Programs, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Algorithms, Mathematical and Computational Engineering