Neural-Based Orthogonal Data Fitting: The Exin Neural Networks Giansalvo Cirrincione

ISBN: 9781118097748

Published: April 6th 2011

ebook

255 pages


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Neural-Based Orthogonal Data Fitting: The Exin Neural Networks  by  Giansalvo Cirrincione

Neural-Based Orthogonal Data Fitting: The Exin Neural Networks by Giansalvo Cirrincione
April 6th 2011 | ebook | PDF, EPUB, FB2, DjVu, talking book, mp3, ZIP | 255 pages | ISBN: 9781118097748 | 4.58 Mb

The presentation of a novel theory in orthogonal regressionThe literature about neural-based algorithms is often dedicated to principal component analysis (PCA) and considers minor component analysis (MCA) a mere consequence. Breaking the mold,MoreThe presentation of a novel theory in orthogonal regressionThe literature about neural-based algorithms is often dedicated to principal component analysis (PCA) and considers minor component analysis (MCA) a mere consequence.

Breaking the mold, Neural-Based Orthogonal Data Fitting is the first book to start with the MCA problem and arrive at important conclusions about the PCA problem.The book proposes several neural networks, all endowed with a complete theory that not only explains their behavior, but also compares them with the existing neural and traditional algorithms. EXIN neurons, which are of the authors invention, are introduced, explained, and analyzed. Further, it studies the algorithms as a differential geometry problem, a dynamic problem, a stochastic problem, and a numerical problem.

It demonstrates the novel aspects of its main theory, including its applications in computer vision and linear system identification. The book shows both the derivation of the TLS EXIN from the MCA EXIN and the original derivation, as well as:Shows TLS problems and gives a sketch of their history and applicationsPresents MCA EXIN and compares it with the other existing approachesIntroduces the TLS EXIN neuron and the SCG and BFGS acceleration techniques and compares them with TLS GAOOutlines the GeTLS EXIN theory for generalizing and unifying the regression problemsEstablishes the GeMCA theory, starting with the identification of GeTLS EXIN as a generalization eigenvalue problemIn dealing with mathematical and numerical aspects of EXIN neurons, the book is mainly theoretical.

All the algorithms, however, have been used in analyzing real-time problems and show accurate solutions. Neural-Based Orthogonal Data Fitting is useful for statisticians, applied mathematics experts, and engineers.



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