{"product_id":"9781118097748","title":"Neural-Based Orthogonal Data Fitting: The EXIN Neural Networks","description":"\u003cb\u003eThe presentation of a novel theory in orthogonal regression\u003c\/b\u003e \u003cp\u003eThe 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, \u003ci\u003eNeural-Based Orthogonal Data Fitting\u003c\/i\u003e is the first book to start with the MCA problem and arrive at important conclusions about the PCA problem.\u003c\/p\u003e \u003cp\u003eThe 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:\u003c\/p\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eShows TLS problems and gives a sketch of their history and applications\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003ePresents MCA EXIN and compares it with the other existing approaches\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eIntroduces the TLS EXIN neuron and the SCG and BFGS acceleration techniques and compares them with TLS GAO\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eOutlines the GeTLS EXIN theory for generalizing and unifying the regression problems\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eEstablishes the GeMCA theory, starting with the identification of GeTLS EXIN as a generalization eigenvalue problem\u003c\/p\u003e \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eIn 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. \u003ci\u003eNeural-Based Orthogonal Data Fitting\u003c\/i\u003e is useful for statisticians, applied mathematics experts, and engineers.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47118301495536,"sku":"9781118097748","price":109.95,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0737\/7593\/9824\/files\/9781118097748_p0.jpg?v=1763692798","url":"https:\/\/shop-qa.barnesandnoble.com\/products\/9781118097748","provider":"Barnes \u0026 Noble (DEV)","version":"1.0","type":"link"}