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Author:   Branko Kovacevic ,  Zeljko Durovic
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   2nd ed. 2008
Dimensions:   Width: 15.50cm , Height: 2.80cm , Length: 23.50cm
Weight:   0.910kg
ISBN:  

9783540709909

ISBN 10:   3540709908
Pages:   380
Publication Date:   15 August 2008
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Out of stock  
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Table of Contents

Review of The Theory of Probability and Random Variables.- Fundamentals of Stochastic Processes.- Linear Discrete-Time Stochastic Systems.- Linear Continuous Time Stochastic Systems.- Fundamentals of Estimation.- Optimum Nonrecursive Linear Estimation: Wiener Filtering.- Optimum Recursive Linear Estimation: Kalman Filtering.- Extensions of The Optimum Recursive (Kalman) Filter.

Reviews

From the reviews of the second edition: In the present textbook basic concepts of linear stochastic systems, stochastic signals, modeling and analysis, as well as model-based signal processing are described using the transfer function model and the state space model. ... Many worked examples are given within the text. The book is suitable for undergraduate and graduate courses in the field of linear stochastic systems, signal processing and automatic control. (Kurt Marti, Zentralblatt MATH, Vol. 1156, 2009) The book presents the fundamentals of stochastic processes and systems, with emphasis on estimation theory. It is appropriate for both undergraduate and graduate students and for engineers in the fields of communications, signal processing, and automatic control. It contains several examples and experiments performed by using Matlab. ... Appendices on Laplace and Z-transforms, matrix analysis, and probability density functions and references end the book. --- (Antonio Napolitano, Mathematical Reviews, Issue 2010 j)

From the reviews of the second edition: In the present textbook basic concepts of linear stochastic systems, stochastic signals, modeling and analysis, as well as model-based signal processing are described using the transfer function model and the state space model. ... Many worked examples are given within the text. The book is suitable for undergraduate and graduate courses in the field of linear stochastic systems, signal processing and automatic control. (Kurt Marti, Zentralblatt MATH, Vol. 1156, 2009) The book presents the fundamentals of stochastic processes and systems, with emphasis on estimation theory. It is appropriate for both undergraduate and graduate students and for engineers in the fields of communications, signal processing, and automatic control. It contains several examples and experiments performed by using Matlab. ... Appendices on Laplace and Z-transforms, matrix analysis, and probability density functions and references end the book. (Antonio Napolitano, Mathematical Reviews, Issue 2010 j)

From the reviews of the second edition: In the present textbook basic concepts of linear stochastic systems, stochastic signals, modeling and analysis, as well as model-based signal processing are described using the transfer function model and the state space model. ! Many worked examples are given within the text. The book is suitable for undergraduate and graduate courses in the field of linear stochastic systems, signal processing and automatic control. (Kurt Marti, Zentralblatt MATH, Vol. 1156, 2009) The book presents the fundamentals of stochastic processes and systems, with emphasis on estimation theory. It is appropriate for both undergraduate and graduate students and for engineers in the fields of communications, signal processing, and automatic control. It contains several examples and experiments performed by using Matlab. ! Appendices on Laplace and Z-transforms, matrix analysis, and probability density functions and references end the book. (Antonio Napolitano, Mathematical Reviews, Issue 2010 j)

From the reviews of the second edition: In the present textbook basic concepts of linear stochastic systems, stochastic signals, modeling and analysis, as well as model-based signal processing are described using the transfer function model and the state space model. ! Many worked examples are given within the text. The book is suitable for undergraduate and graduate courses in the field of linear stochastic systems, signal processing and automatic control. (Kurt Marti, Zentralblatt MATH, Vol. 1156, 2009)

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