Springer Statistical Signal Processing: Frequency Estimation

Product Description This book introduces readers to various signal processing models that have been used in analyzing periodic data, and discusses the statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical observations. The received signals are usually disturbed by thermal, electrical, atmospheric or intentional interferences, and due to their random nature, statistical techniques play an important role in their analysis. Statistics is also used in the formulation of appropriate models to describe the behavior of systems, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Analyzing different real-world data sets to illustrate how different models can be used in practice, and highlighting open problems for future research, the book is a valuable resource for senior undergraduate and graduate students specializing in mathematics or statistics. From the Back Cover This book introduces readers to various signal processing models that have been used in analyzing periodic data, and discusses the statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical observations. The received signals are usually disturbed by thermal, electrical, atmospheric or intentional interferences, and due to their random nature, statistical techniques play an important role in their analysis. Statistics is also used in the formulation of appropriate models to describe the behavior of systems, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Analyzing different real-world data sets to illustrate how different models can be used in practice, and highlighting open problems for future research, the book is a valuable resource for senior undergraduate and graduate students specializing in mathematics or statistics. About the Author Professor Debasis Kundu received his B-Stat and M-Stat from the Indian Statistical Institute in 1982 and 1984, respectively, MA in Mathematics from the University of Pittsburgh in 1985 and Ph.D. from the Pennsylvania State University in 1989 under the guidance of Professor C.R. Rao. After finishing his Ph.D. he joined The University of Texas at Dallas as an Assistant Professor before joining Indian Institute of Technology Kanpur in 1990. He served as the Head of the Department of Mathematics and Statistics, IIT Kanpur from 2011 to 2014, currently he is the Dean of Faculty Affairs at IIT Kanpur. Professor Kundu works on different areas of Statistics. His major research interests are on Distribution Theory, Lifetime Data Analysis, Censoring, Statistical Signal Processing and Statistical Computing. He has published more than 300 research papers in different refereed journals with close to 12,000 citations and H-index 55. He has supervised/ co-supervised 14 Ph.D. and 5 M.Tech students. He has co-authored two research monographs on Statistical Signal Processing and on Step-Stress Models, and co-edited one book on Statistical Computing. He is a Fellow of the National Academy of Sciences, India and a Fellow of the Indian Society of Probability and Statistics. He has received Chandana Award from the Canadian Mathematical Society, Distinguished Statistician Award from the Indian Society of Probability and Statistics, P.C. Mahalanobis Award from the Indian Society of Operation Research and Distinguished Teacher’s Award from IIT Kanpur. He is currently the Editor-in-Chief of the Journal of the Indian Society of Probability and Statistics, and in the editorial boards of Communications in Statistics - Theory and Methods, Communications in Statistics - Simulation and Computation, Communications in Statistics - Case Studies and Sankhya, Ser. B. He has served as members in the editorial boards of the IEEE Transactions