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Statistical signal processing = freq...

Nandi, Swagata.

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Statistical signal processing = frequency estimation /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Statistical signal processing/ by Swagata Nandi, Debasis Kundu.
其他題名:	frequency estimation /
作者:	Nandi, Swagata.
其他作者:	Kundu, Debasis.
出版者:	Singapore :Springer Singapore : : 2020.,
面頁冊數:	xxiii, 265 p. :ill., digital ;24 cm.
內容註:	Introduction -- Preliminaries -- Methods of Estimation - Iterative -- Methods of Estimation - Non-iterative -- Asymptotic Results (of Sinusoidal model) -- Order estimation -- Fundamental Frequency Model and its generalization -- Data Analysis -- Two dimensional and multidimensional models -- Chirp Signal Model -- Random Amplitudes -- Related Models -- Appendices.
Contained By:	Springer Nature eBook
標題:	Signal processing - Statistical methods. -
電子資源:	https://doi.org/10.1007/978-981-15-6280-8
ISBN:	9789811562808

Statistical signal processing = frequency estimation /
Nandi, Swagata.

Statistical signal processingfrequency estimation /[electronic resource] :by Swagata Nandi, Debasis Kundu. - Second edition. - Singapore :Springer Singapore :2020. - xxiii, 265 p. :ill., digital ;24 cm.

Introduction -- Preliminaries -- Methods of Estimation - Iterative -- Methods of Estimation - Non-iterative -- Asymptotic Results (of Sinusoidal model) -- Order estimation -- Fundamental Frequency Model and its generalization -- Data Analysis -- Two dimensional and multidimensional models -- Chirp Signal Model -- Random Amplitudes -- Related Models -- Appendices.

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.

ISBN: 9789811562808

Standard No.: 10.1007/978-981-15-6280-8doiSubjects--Topical Terms:

649787
Signal processing
--Statistical methods.

LC Class. No.: TK5102.9 / .N363 2020

Dewey Class. No.: 621.3822

Statistical signal processing = frequency estimation /
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505 0 $a Introduction -- Preliminaries -- Methods of Estimation - Iterative -- Methods of Estimation - Non-iterative -- Asymptotic Results (of Sinusoidal model) -- Order estimation -- Fundamental Frequency Model and its generalization -- Data Analysis -- Two dimensional and multidimensional models -- Chirp Signal Model -- Random Amplitudes -- Related Models -- Appendices.
520 $a 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.
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