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＜電子ブック＞
Statistical Signal Processing : Frequency Estimation / by Debasis Kundu, Swagata Nandi
(SpringerBriefs in Statistics. ISSN:21915458)

版	1st ed. 2012.
出版者	New Delhi : Springer India : Imprint: Springer
出版年	2012
本文言語	英語
大きさ	XVII, 132 p. 21 illus : online resource
著者標目	*Kundu, Debasis author Nandi, Swagata author SpringerLink (Online service)
件　名	LCSH:Mathematical statistics -- Data processing  全ての件名で検索 LCSH:Statistics  LCSH:Algorithms LCSH:Engineering mathematics LCSH:Engineering -- Data processing  全ての件名で検索 FREE:Statistics and Computing FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences FREE:Algorithms FREE:Mathematical and Computational Engineering Applications
一般注記	1 Introduction -- 2 Notations and Preliminaries -- 3 Estimation of Frequencies -- 4 Asymptotic Properties -- 5 Estimating the Number of Components -- 6 Real Data Example -- 7 Multidimensional Models -- 8 Related Models -- References -- Index Signal processing may broadly be considered to involve the recovery of information from physical observations. The received signal is usually disturbed by thermal, electrical, atmospheric or intentional interferences. Due to the random nature of the signal, statistical techniques play an important role in analyzing the signal. Statistics is also used in the formulation of the appropriate models to describe the behavior of the system, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Statistical signal processing basically refers to the analysis of random signals using appropriate statistical techniques. The main aim of this book is to introduce different signal processing models which have been used in analyzing periodic data, and different statistical and computational issues involved in solving them. We discuss in detail the sinusoidal frequency model which has been used extensively in analyzing periodic data occuring in various fields. We have tried to introduce different associated models and higher dimensional statistical signal processing models which have been further discussed in the literature. Different real data sets have been analyzed to illustrate how different models can be used in practice. Several open problems have been indicated for future research HTTP:URL=https://doi.org/10.1007/978-81-322-0628-6

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