Generalized matrix inversion machine de stanimirovi predrag (3 resultados)

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  • Idioma: Inglés

    Editorial: Springer-Verlag Gmbh Jan 2026, 2026

    3032014921 / 9783032014924

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    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

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    Condición: Nuevo

    EUR 213,99

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    Cantidad disponible: 2 disponibles

    Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a comprehensive exploration of the dynamical system approach in numerical linear algebra, with a special focus on computing generalized inverses, solving systems of linear equations, and addressing linear matrix equations. Bridging four major scientific domains numerical linear algebra, recurrent neural networks (RNNs), dynamical systems, and unconstrained nonlinear optimization this book offers a unique, interdisciplinary perspective.Generalized Matrix Inversion: A Machine Learning Approach explores the theory and application of recurrent neural networks, particularly continuous-time recurrent neural networks (CTRNNs), which use systems of ordinary differential equations to model the influence of inputs on neurons. Special attention is given to CTRNNs designed for finding zeros of equations or minimizing nonlinear functions, with detailed coverage of two important classes: Gradient Neural Networks (GNN) and Zhang (Zeroing) Neural Networks (ZNN). Both time-varying and time-invariant models are examined across scalar, vector, and matrix cases.Based on the authors research that has been published in leading scientific journals, the book spans a variety of disciplines, including linear and multilinear algebra, generalized inverses, recurrent neural networks, dynamical systems, time-varying problem solving, and unconstrained nonlinear optimization. Readers will find a global overview of activation functions, rigorous convergence analysis, and innovative improvements in the definition of error functions for GNN and ZNN dynamic systems.Generalized Matrix Inversion: A Machine Learning Approachis an essential resource for researchers and practitioners seeking advanced methods at the intersection of machine learning, optimization, and matrix computation. 333 pp. Englisch.…

  • Idioma: Inglés

    Editorial: Palgrave Macmillan, 2026

    3032014921 / 9783032014924

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 220,55

    Envío por EUR 35,00 
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    Cantidad disponible: 1 disponible

    Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a comprehensive exploration of the dynamical system approach in numerical linear algebra, with a special focus on computing generalized inverses, solving systems of linear equations, and addressing linear matrix equations. Bridging four major scientific domains numerical linear algebra, recurrent neural networks (RNNs), dynamical systems, and unconstrained nonlinear optimization this book offers a unique, interdisciplinary perspective.Generalized Matrix Inversion: A Machine Learning Approach explores the theory and application of recurrent neural networks, particularly continuous-time recurrent neural networks (CTRNNs), which use systems of ordinary differential equations to model the influence of inputs on neurons. Special attention is given to CTRNNs designed for finding zeros of equations or minimizing nonlinear functions, with detailed coverage of two important classes: Gradient Neural Networks (GNN) and Zhang (Zeroing) Neural Networks (ZNN). Both time-varying and time-invariant models are examined across scalar, vector, and matrix cases.Based on the authors research that has been published in leading scientific journals, the book spans a variety of disciplines, including linear and multilinear algebra, generalized inverses, recurrent neural networks, dynamical systems, time-varying problem solving, and unconstrained nonlinear optimization. Readers will find a global overview of activation functions, rigorous convergence analysis, and innovative improvements in the definition of error functions for GNN and ZNN dynamic systems.Generalized Matrix Inversion: A Machine Learning Approachis an essential resource for researchers and practitioners seeking advanced methods at the intersection of machine learning, optimization, and matrix computation.…

  • Idioma: Inglés

    Editorial: Springer, Springer Jan 2026, 2026

    3032014921 / 9783032014924

    • Tapa dura
    • Impresión bajo demanda

    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

    Vendedor de 5 estrellas
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    Condición: Nuevo

    EUR 213,99

    Envío por EUR 60,00 
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    Cantidad disponible: 1 disponible

    Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -1. Background Information.- 2 Gradient Neural Network (GNN) and their Modifications.- 3 Zeroing Neural Network (ZNN).- 4 From iterations to ZNNs and vice versa, 5 Modified ZNN dynamical systems.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 372 pp. Englisch. …