Radial Basis Function Networks (88 results)

Condition: New. pp. 180.

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Taschenbuch. Condition: Neu. Data mining for performance of vegetative filter strips | A comparison between prediction models : artificial neural networks (back propagation & radial basis function) vs. GRAPH | Sanyogita Andriyas | Taschenbuch | 216 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9783659506154 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.…

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Condition: Sehr gut. Zustand: Sehr gut | Seiten: 340 | Sprache: Englisch | Produktart: Bücher | The Radial Basis Function (RBF) neural network has gained in popularity over recent years because of its rapid training and its desirable properties in classification and functional approximation applications. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of application areas, for example, robotics, biomedical engineering, and the financial sector. The two volumes provide a comprehensive survey of the latest developments in this area. Volume 1 covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms, for example RBF learning using genetic algorithms. Both volumes will prove extremely useful to practitioners in the field, engineers, researchers and technically accomplished managers.…

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Condition: New. This title deals with the design of Radial Basis Function Networks (RBFNs), one of two classes of feedforward networks with applications in artificial neural networks, for particular tasks. These applications are in such engineering problems as nonlinear process estimation and control. Series: Adaptive and Learning Systems for Signal Processing, Communications and Control Series. Num Pages: 208 pages, references. BIC Classification: TJK; UT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 242 x 165 x 17. Weight in Grams: 444. . 2001. Hardback. . . . .…

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Condition: New. Presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications. This work also includes a detailed review of system identification, including indirect and direct adaptive control of nonlinear systems using neural networks. Editor(s): Sundararajan, N.; Saratchandran, P.; Yan, Li. Series: The International Series on Asian Studies in Computer and Information Science. Num Pages: 174 pages, biography. BIC Classification: TJFM; UYQN. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 234 x 156 x 11. Weight in Grams: 950. . 2001. Hardback. . . . .…

Taschenbuch. Condition: Neu. Fully Tuned Radial Basis Function Neural Networks for Flight Control | N. Sundararajan (u. a.) | Taschenbuch | xvi | Englisch | 2010 | Springer US | EAN 9781441949158 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Fully Tuned Radial Basis Function Neural Networks for Flight Control presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications. A Lyapunov synthesis approach is used to derive the tuning rules for the RBF controller parameters in order to guarantee the stability of the closed loop system. Unlike previous methods that tune only the weights of the RBF network, this book presents the derivation of the tuning law for tuning the centers, widths, and weights of the RBF network, and compares the results with existing algorithms. It also includes a detailed review of system identification, including indirect and direct adaptive control of nonlinear systems using neural networks. Fully Tuned Radial Basis Function Neural Networks for Flight Control is an excellent resource for professionals using neural adaptive controllers for flight control applications.…

Condition: New. To serve as a bridge between nonparametric estimation and artificial neural networks, Yee.and Haykin.examines the interplay of ides in the two ideas. (SciTech Book News Vol. 25, No. 2 June 2001)Simon Haykin is a well-known author of books on neura.

Condition: New. pp. 176.

Condition: Sehr gut. Zustand: Sehr gut | Seiten: 384 | Sprache: Englisch | Produktart: Bücher | The Radial Basis Function (RBF) network has gained in popularity in recent years. This is due to its desirable properties in classification and functional approximation applications, accompanied by training that is more rapid than that of many other neural-network techniques. RBF network research has focused on enhanced training algorithms and variations on the basic architecture to improve the performance of the network. In addition, the RBF network is proving to be a valuable tool in a diverse range of applications areas, for example, robotics, biomedical engineering, and the financial sector. The two-title series Theory and Applications of Radial Basis Function Networks provides a comprehensive survey of recent RBF network research. This volume, New Advances in Design, contains a wide range of applications in the laboratory and case-studies describing current use. The sister volume to this one, Recent Developments in Theory and Applications, covers advances in training algorithms, variations on the architecture and function of the basis neurons, and hybrid paradigms. The combination of the two volumes will prove extremely useful to practitioners in the field, engineers, researchers, students and technically accomplished managers.…

Condition: New. pp. 180.

Condition: New. pp. 384.