Approximate and Noisy Realization of Discrete-Time Dynamical Systems

This monograph deals with approximation and noise cancellation of dynamical systems which include linear and nonlinear input/output relations. It will be of special interest to researchers, engineers and graduate students who have specialized in ?ltering theory and system theory. From noisy or noiseless data, reductionwillbemade.Anewmethodwhichreducesnoiseormodelsinformation will be proposed. Using this method will allow model description to be treated as noise reduction or model reduction. As proof of the e?cacy, this monograph provides new results and their extensions which can also be applied to nonlinear dynamical systems. To present the e?ectiveness of our method, many actual examples of noise and model information reduction will also be provided. Using the analysis of state space approach, the model reduction problem may have become a major theme of technology after 1966 for emphasizing e?ciency in the ?elds of control, economy, numerical analysis, and others. Noise reduction problems in the analysis of noisy dynamical systems may havebecomeamajorthemeoftechnologyafter1974foremphasizinge?ciencyin control.However,thesubjectsoftheseresearcheshavebeenmainlyconcentrated in linear systems. In common model reduction of linear systems in use today, a singular value decompositionofaHankelmatrixisusedto?ndareducedordermodel.However, the existence of the conditions of the reduced order model are derived without evaluationoftheresultantmodel.Inthecommontypicalnoisereductionoflinear systems in use today, the order and parameters of the systems are determined by minimizing information criterion. Approximate and noisy realization problems for input/output relations can be roughly stated as follows: A. The approximate realization problem. For any input/output map,?nd one mathematical model such that it is similar totheinput/outputmapandhasalowerdimensionthanthegivenminimalstate spaceofadynamicalsystemwhichhasthesamebehaviortotheinput/outputmap. B. The noisy realization problem.

List of contents

Input/Output Map and Additive Noises.- Approximate and Noisy Realization of Linear Systems.- Approximate and Noisy Realization of So-called Linear Systems.- Approximate and Noisy Realization of Almost Linear Systems.- Approximate and Noisy Realization of Pseudo Linear Systems.- Approximate and Noisy Realization of Affine Dynamical Systems.- Approximate and Noisy Realization of Linear Representation Systems.

Summary

This monograph deals with approximation and noise cancellation of dynamical systems which include linear and nonlinear input/output relations. It will be of special interest to researchers, engineers and graduate students who have specialized in ?ltering theory and system theory. From noisy or noiseless data, reductionwillbemade.Anewmethodwhichreducesnoiseormodelsinformation will be proposed. Using this method will allow model description to be treated as noise reduction or model reduction. As proof of the e?cacy, this monograph provides new results and their extensions which can also be applied to nonlinear dynamical systems. To present the e?ectiveness of our method, many actual examples of noise and model information reduction will also be provided. Using the analysis of state space approach, the model reduction problem may have become a major theme of technology after 1966 for emphasizing e?ciency in the ?elds of control, economy, numerical analysis, and others. Noise reduction problems in the analysis of noisy dynamical systems may havebecomeamajorthemeoftechnologyafter1974foremphasizinge?ciencyin control.However,thesubjectsoftheseresearcheshavebeenmainlyconcentrated in linear systems. In common model reduction of linear systems in use today, a singular value decompositionofaHankelmatrixisusedto?ndareducedordermodel.However, the existence of the conditions of the reduced order model are derived without evaluationoftheresultantmodel.Inthecommontypicalnoisereductionoflinear systems in use today, the order and parameters of the systems are determined by minimizing information criterion. Approximate and noisy realization problems for input/output relations can be roughly stated as follows: A. The approximate realization problem. For any input/output map,?nd one mathematical model such that it is similar totheinput/outputmapandhasalowerdimensionthanthegivenminimalstate spaceofadynamicalsystemwhichhasthesamebehaviortotheinput/outputmap. B. The noisy realization problem.

Additional text

From the reviews:

"In this monograph new interesting results concerning the following two problems are presented. Approximate realization problem: For any given input/output map without noise … . Noisy realization problem: For any given input/output map with noise … . A new method called the constrained least square method is proposed to solve the problems. … This monograph can be recommended first of all to scientists and Phd students with good mathematical backgrounds." (Tadeusz Kaczorek, Zentralblatt MATH, Vol. 1147, 2008)

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From the reviews:

"In this monograph new interesting results concerning the following two problems are presented. Approximate realization problem: For any given input/output map without noise ... . Noisy realization problem: For any given input/output map with noise ... . A new method called the constrained least square method is proposed to solve the problems. ... This monograph can be recommended first of all to scientists and Phd students with good mathematical backgrounds." (Tadeusz Kaczorek, Zentralblatt MATH, Vol. 1147, 2008)

Product details

• Authors: Yasumichi Hasegawa
• Publisher: Springer, Berlin
• Languages: English
• Product format: Paperback / Softback
• Released: 19.02.2009
• EAN: 9783540794332
• ISBN: 978-3-540-79433-2
• No. of pages: 248
• Dimensions: 159 mm x 14 mm x 233 mm
• Weight: 372 g
• Illustrations: VIII, 248 p. 70 illus.
• Series: Lecture Notes in Control and Information Sciences; Lecture Notes in Control and Information Sciences
• Subject: Natural sciences, medicine, IT, technology > Technology > Electronics, electrical engineering, communications engineering