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Cyclostationary processes and time series
theory, applications, and generalizations
1 online resource (xxxv, 590 pages) : illustrations
Many processes in nature arise from the interaction of periodic phenomena with random phenomena. The results are processes that are not periodic, but whose statistical functions are periodic functions of time. These processes are called cyclostationary and are an appropriate mathematical model for signals encountered in many fields including communications, radar, sonar, telemetry, acoustics, mechanics, econometrics, astronomy, and biology.
About the Author -- Preface -- Acknowledgement -- List of Abbreviations -- Notation -- Part 1. Cyclostationarity -- Part 2. Generalizations -- Bibliography -- Index
Antonio Napolitano, University of Napoli "Parthenope," Department of Engineering, Napoli, Italy
Includes bibliographical references (pages 525-586) and index
Antonio Napolitano is Full Professor of Telecommunications at the University of Napoli Parthenope (Italy). In 1995 he received the Best Paper of the Year Award from the European Association for Signal Processing (EURASIP) for a paper on higher-order cyclostationarity. In 2007 was recipient of the EURASIP Best Paper Award for a paper on the functional approach in signal analysis. In 2008 he received from Elsevier the Most Cited Paper Award for a review article on cyclostationarity. In 2016 he became an IEEE Fellow. He has been Associate Editor of the IEEE Transactions on Signal Processing and is on the Editorial Board of Signal Processing (Elsevier) and Digital Signal Processing (Elsevier). He has been in the Signal Processing Theory and Methods Technical Committees (SPM-TC) and is now in the Sensor Array and Multichannel Technical Committee (SAM-TC) of the IEEE Signal Processing Society.
London [England] ; San Diego, CA : Academic Press, [2020]