Adaptive nonlinear system identification : the Volterra and Wiener model approaches /

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Bibliographic Details
Author / Creator:Ogunfunmi, Tokunbo.
Imprint:New York ; [London] : Springer, c2007.
Description:1 online resource (xv, 229 p.) : ill.
Language:English
Series:Signals and communication technology
Signals and communication technology.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/8880916
Hidden Bibliographic Details
ISBN:9780387686301
0387686304
9780387263281 (hbk.)
0387263284 (hbk.)
9786611042820
6611042822
Notes:Includes bibliographical references and index.
Description based on print version record.
Summary:"Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches introduces engineers and researchers to the field of nonlinear adaptive system identification. The book includes recent research results in the area of adaptive nonlinear system identification and presents simple, concise, easy-to-understand methods for identifying nonlinear systems. These methods use adaptive filter algorithms that are well known for linear systems identification. They are applicable for nonlinear systems that can be efficiently modeled by polynomials." "Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches is useful to graduate students, engineers and researchers in the areas of nonlinear systems, control, biomedical systems and in adaptive signal processing."--Jacket.
Other form:Print version: Ogunfunmi, Tokunbo. Adaptive nonlinear system identification. New York ; [London] : Springer, c2007 9780387263281 0387263284
Description
Summary:

Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches introduces engineers and researchers to the field of nonlinear adaptive system identification. The book includes recent research results in the area of adaptive nonlinear system identification and presents simple, concise, easy-to-understand methods for identifying nonlinear systems. These methods use adaptive filter algorithms that are well known for linear systems identification. They are applicable for nonlinear systems that can be efficiently modeled by polynomials.

After a brief introduction to nonlinear systems and to adaptive system identification, the author presents the discrete Volterra model approach. This is followed by an explanation of the Wiener model approach. Adaptive algorithms using both models are developed. The performance of the two methods are then compared to determine which model performs better for system identification applications.

Adaptive Nonlinear System Identification: The Volterra and Wiener Model Approaches is useful to graduates students, engineers and researchers in the areas of nonlinear systems, control, biomedical systems and in adaptive signal processing.

Physical Description:1 online resource (xv, 229 p.) : ill.
Bibliography:Includes bibliographical references and index.
ISBN:9780387686301
0387686304
9780387263281
0387263284
9786611042820
6611042822