ISBN: 9780080551357

Optimization Techniques is a unique reference source to a diverse array of methods for achieving optimization, and includes both systems structures and computational methods. The text dev… Plus…

Optimization Techniques is a unique reference source to a diverse array of methods for achieving optimization, and includes both systems structures and computational methods. The text devotes broad coverage toa unified view of optimal learning, orthogonal transformation techniques, sequential constructive techniques, fast back propagation algorithms, techniques for neural networks with nonstationary or dynamic outputs, applications to constraint satisfaction,optimization issues and techniques for unsupervised learning neural networks, optimum Cerebellar Model of Articulation Controller systems, a new statistical theory of optimum neural learning, and the role of the Radial Basis Function in nonlinear dynamical systems.This volume is useful for practitioners, researchers, and students in industrial, manufacturing, mechanical, electrical, and computer engineering.Key Features* Provides in-depth treatment of theoretical contributions to optimal learning for neural network systems* Offers a comprehensive treatment of orthogonal transformation techniques for the optimization of neural network systems* Includes illustrative examples and comprehensive treatment of sequential constructive techniques for optimization of neural network systems* Presents a uniquely comprehensive treatment of the highly effective fast back propagation algorithms for the optimization of neural network systems* Treats, in detail, optimization techniques for neural network systems with nonstationary or dynamic inputs* Covers optimization techniques and applications of neural network systems in constraint satisfaction; PDF; Scientific, Technical and Medical > Technology: general issues > Maths for engineers, Elsevier Science<

ISBN: 9780080551357

Optimization Techniques is a unique reference source to a diverse array of methods for achieving optimization, and includes both systems structures and computational methods. The text dev… Plus…

Optimization Techniques is a unique reference source to a diverse array of methods for achieving optimization, and includes both systems structures and computational methods. The text devotes broad coverage toa unified view of optimal learning, orthogonal transformation techniques, sequential constructive techniques, fast back propagation algorithms, techniques for neural networks with nonstationary or dynamic outputs, applications to constraint satisfaction,optimization issues and techniques for unsupervised learning neural networks, optimum Cerebellar Model of Articulation Controller systems, a new statistical theory of optimum neural learning, and the role of the Radial Basis Function in nonlinear dynamical systems.This volume is useful for practitioners, researchers, and students in industrial, manufacturing, mechanical, electrical, and computer engineering.Provides in-depth treatment of theoretical contributions to optimal learning for neural network systemsOffers a comprehensive treatment of orthogonal transformation techniques for the optimization of neural network systemsIncludes illustrative examples and comprehensive treatment of sequential constructive techniques for optimization of neural network systemsPresents a uniquely comprehensive treatment of the highly effective fast back propagation algorithms for the optimization of neural network systemsTreats, in detail, optimization techniques for neural network systems with nonstationary or dynamic inputsCovers optimization techniques and applications of neural network systems in constraint satisfaction; PDF; Scientific, Technical and Medical > Science: general issues > Maths for scientists, Elsevier Science<

ISBN: 9780080551357

Optimization Techniques is a unique reference source to a diverse array of methods for achieving optimization, and includes both systems structures and computational methods. The text dev… Plus…

Optimization Techniques is a unique reference source to a diverse array of methods for achieving optimization, and includes both systems structures and computational methods. The text devotes broad coverage toa unified view of optimal learning, orthogonal transformation techniques, sequential constructive techniques, fast back propagation algorithms, techniques for neural networks with nonstationary or dynamic outputs, applications to constraint satisfaction, optimization issues and techniques for unsupervised learning neural networks, optimum Cerebellar Model of Articulation Controller systems, a new statistical theory of optimum neural learning, and the role of the Radial Basis Function in nonlinear dynamical systems.This volume is useful for practitioners, researchers, and students in industrial, manufacturing, mechanical, electrical, and computer engineering. Provides in-depth treatment of theoretical contributions to optimal learning for neural network systems Offers a comprehensive treatment of orthogonal transformation techniques for the optimization of neural network systems Includes illustrative examples and comprehensive treatment of sequential constructive techniques for optimization of neural network systems Presents a uniquely comprehensive treatment of the highly effective fast back propagation algorithms for the optimization of neural network systems Treats, in detail, optimization techniques for neural network systems with nonstationary or dynamic inputs Covers optimization techniques and applications of neural network systems in constraint satisfaction Academic Press Zoology 9780124438620 DE,GB,ES,IT,FR English Biological Sciences, Elsevier Science<

ISBN: 9780080551357

Optimization Techniques is a unique reference source to a diverse array of methods for achieving optimization, and includes both systems structures and computational methods. The text dev… Plus…

Optimization Techniques is a unique reference source to a diverse array of methods for achieving optimization, and includes both systems structures and computational methods. The text devotes broad coverage toa unified view of optimal learning, orthogonal transformation techniques, sequential constructive techniques, fast back propagation algorithms, techniques for neural networks with nonstationary or dynamic outputs, applications to constraint satisfaction,optimization issues and techniques for unsupervised learning neural networks, optimum Cerebellar Model of Articulation Controller systems, a new statistical theory of optimum neural learning, and the role of the Radial Basis Function in nonlinear dynamical systems.This volume is useful for practitioners, researchers, and students in industrial, manufacturing, mechanical, electrical, and computer engineering. Optimization & Neural Networks & Artificial Intelligence, Expert Systems and Knowledge-Based Systems & Software Engineering & ENGENHARIA - TEMAS ATUAIS & Optimization & Artificial Intelligence, Expert Systems and Knowledge-Based Systems & Neural Networks & Software Engineering & Computer Science, [PU: Pergamon; Pergamon Press]<

ISBN: 9780080551357

Optimization Techniques ab 147.56 EURO Medien > Bücher, [PU: Pergamon; Pergamon Press]