Alma y alanis (75 risultati)

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Paperback. Condizione: Brand New. 246 pages. 9.21x6.14x0.47 inches. In Stock.

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Condizione: New. Nancy Arana-Daniel received her B.Sc. Degree from the University of Guadalajara in 2000, and her M. Sc. And Ph.D. degrees in electric engineering with the special field in computer science from Research Center of the National Polytechnic.

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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Neural networks have become a well-established methodology as exempli ed by their applications to identi cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o ers a better suited tool to model and control of nonlinear systems. There exist di erent training algorithms for neural networks, which, h- ever, normally encounter some technical problems such as local minima, slow learning, and high sensitivity to initial conditions, among others. As a viable alternative, new training algorithms, for example, those based on Kalman ltering, have been proposed. There already exists publications about trajectory tracking using neural networks; however, most of those works were developed for continuous-time systems. On the other hand, while extensive literature is available for linear discrete-timecontrolsystem,nonlineardiscrete-timecontroldesigntechniques have not been discussed to the same degree. Besides, discrete-time neural networks are better tted for real-time implementations.…

Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Neural networks have become a well-established methodology as exempli ed by their applications to identi cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o ers a better suited tool to model and control of nonlinear systems. There exist di erent training algorithms for neural networks, which, h- ever, normally encounter some technical problems such as local minima, slow learning, and high sensitivity to initial conditions, among others. As a viable alternative, new training algorithms, for example, those based on Kalman ltering, have been proposed. There already exists publications about trajectory tracking using neural networks; however, most of those works were developed for continuous-time systems. On the other hand, while extensive literature is available for linear discrete-timecontrolsystem,nonlineardiscrete-timecontroldesigntechniques have not been discussed to the same degree. Besides, discrete-time neural networks are better tted for real-time implementations.…

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Paperback. Condizione: Brand New. 152 pages. 9.00x6.00x0.50 inches. In Stock.

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Taschenbuch. Condizione: Neu. Discrete-Time Neural Observers | Analysis and Applications | Alma Y Alanis (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2017 | Elsevier Inc | EAN 9780128105436 | Verantwortliche Person für die EU: Kolibri 360 GmbH, Ettore-Bugatti-Str. 6-14, 51149 Köln, produktsicherheit[at]kolibri360[dot]de | Anbieter: preigu.…

Condizione: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Neural networks have become a well-established methodology as exempli?ed by their applications to identi?cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o?ers a better suited tool to model and control of nonlinear systems. There exist di?erent training algorithms for neural networks, which, h- ever, normally encounter some technical problems such as local minima, slow learning, and high sensitivity to initial conditions, among others. As a viable alternative, new training algorithms, for example, those based on Kalman ?ltering, have been proposed. There already exists publications about trajectory tracking using neural networks; however, most of those works were developed for continuous-time systems. On the other hand, while extensive literature is available for linear discrete-timecontrolsystem,nonlineardiscrete-timecontroldesigntechniques have not been discussed to the same degree. Besides, discrete-time neural networks are better ?tted for real-time implementations.…

Taschenbuch. Condizione: Neu. Artificial Neural Networks for Engineering Applications | Alma Y Alanis (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2019 | Academic Press | EAN 9780128182475 | Verantwortliche Person für die EU: Elsevier B.V., Radarweg 29, 1043 NX AMSTERDAM, NIEDERLANDE, productsafety[at]elsevier[dot]com | Anbieter: preigu. …