Algebraically Approximate and Noisy Realization of Discrete-Time Systems and Digital Images

Algebraically Approximate and Noisy Realization of Discrete-Time Systems and Digital Images
Author :
Publisher : Springer Science & Business Media
Total Pages : 256
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ISBN-10 : 9783642032172
ISBN-13 : 3642032176
Rating : 4/5 (72 Downloads)

Book Synopsis Algebraically Approximate and Noisy Realization of Discrete-Time Systems and Digital Images by : Yasumichi Hasegawa

Download or read book Algebraically Approximate and Noisy Realization of Discrete-Time Systems and Digital Images written by Yasumichi Hasegawa and published by Springer Science & Business Media. This book was released on 2009-09-30 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph deals with approximation and noise cancellation of dyn- ical systems which include linear and nonlinear input/output relationships. It also deal with approximation and noise cancellation of two dimensional arrays. It will be of special interest to researchers, engineers and graduate students who have specialized in ?ltering theory and system theory and d- ital images. This monograph is composed of two parts. Part I and Part II will deal with approximation and noise cancellation of dynamical systems or digital images respectively. From noiseless or noisy data, reduction will be made. A method which reduces model information or noise was proposed in the reference vol. 376 in LNCIS [Hasegawa, 2008]. Using this method will allow model description to be treated as noise reduction or model reduction without having to bother, for example, with solving many partial di?er- tial equations. This monograph will propose a new and easy method which produces the same results as the method treated in the reference. As proof of its advantageous e?ect, this monograph provides a new law in the sense of numerical experiments. The new and easy method is executed using the algebraic calculations without solving partial di?erential equations. For our purpose,manyactualexamplesofmodelinformationandnoisereductionwill 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.


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