Noise signals : Modelling and Analyses
Language: English
Published by Palgrave Macmillan
- Hardcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
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Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - The book meticulously details a constructive mathematical model of a stochastic noise process, specifically a linear random process and its characteristics. Theoretical reasoning on the relationship between random processes with independent increments and those with independent values, known as random processes of white noise, is provided. The model of a linear random process serves as a mathematical representation of colored noises in various hues. Characteristics of both non-stationary and stationary linear random processes are elucidated, with emphasis on their ergodic properties, crucial for practical applications. The study also encompasses the vector linear random process, portraying a model of multi-channel noise signals. A novel contribution to the theory of random functions is the development of a constructive model of a conditional linear random process. This involves determining its distribution laws in the form of a characteristic function and relevant statistical characteristics, which can serve as potential indicators for identifying stochastic noise processes. The book revisits research on periodic stochastic models, examining cyclic, rhythmic, natural, and artificial phenomena, processes, and signals. A comprehensive analysis of the linear periodic random process is conducted, and the identification characteristics of periodic models of stochastic noise signals are explored. Significant attention is directed toward employing contour and phase methods as a theoretical foundation for addressing narrow-band noise signal identification challenges.…
Seller Inventory # 9783031710926
- Title
- Noise signals : Modelling and Analyses
- Author
- Leonid Scherbak
- Publisher
- Palgrave Macmillan
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3031710924
- ISBN 13
- 9783031710926
- Item weight
- 518 grams
- Dimensions
- 241x160x19 mm
The book meticulously details a constructive mathematical model of a stochastic noise process, specifically a linear random process and its characteristics. Theoretical reasoning on the relationship between random processes with independent increments and those with independent values, known as random processes of white noise, is provided. The model of a linear random process serves as a mathematical representation of colored noises in various hues. Characteristics of both non-stationary and stationary linear random processes are elucidated, with emphasis on their ergodic properties, crucial for practical applications. The study also encompasses the vector linear random process, portraying a model of multi-channel noise signals. A novel contribution to the theory of random functions is the development of a constructive model of a conditional linear random process. This involves determining its distribution laws in the form of a characteristic function and relevant statistical characteristics, which can serve as potential indicators for identifying stochastic noise processes. The book revisits research on periodic stochastic models, examining cyclic, rhythmic, natural, and artificial phenomena, processes, and signals. A comprehensive analysis of the linear periodic random process is conducted, and the identification characteristics of periodic models of stochastic noise signals are explored. Significant attention is directed toward employing contour and phase methods as a theoretical foundation for addressing narrow-band noise signal identification challenges.
"Synopsis" may belong to another edition of this title.
From the Back Cover
The book meticulously details a constructive mathematical model of a stochastic noise process, specifically a linear random process and its characteristics. Theoretical reasoning on the relationship between random processes with independent increments and those with independent values, known as random processes of white noise, is provided. The model of a linear random process serves as a mathematical representation of colored noises in various hues. Characteristics of both non-stationary and stationary linear random processes are elucidated, with emphasis on their ergodic properties, crucial for practical applications. The study also encompasses the vector linear random process, portraying a model of multi-channel noise signals. A novel contribution to the theory of random functions is the development of a constructive model of a conditional linear random process. This involves determining its distribution laws in the form of a characteristic function and relevant statistical characteristics, which can serve as potential indicators for identifying stochastic noise processes. The book revisits research on periodic stochastic models, examining cyclic, rhythmic, natural, and artificial phenomena, processes, and signals. A comprehensive analysis of the linear periodic random process is conducted, and the identification characteristics of periodic models of stochastic noise signals are explored. Significant attention is directed toward employing contour and phase methods as a theoretical foundation for addressing narrow-band noise signal identification challenges.
"About the title" may belong to another edition of this title.
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