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From Thermal Field Theory To Neural Networks

1994, he was only 31.A meeting was organized at CERN, covering the various aspects of his scientific interests: thermal field theory and its;

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Statistical Mechanics of Neural Networks

This book highlights a comprehensive introduction to the fundamental statistical mechanics underneath the inner workings of neural networks;

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Stochastic Models of Neural Networks

This book is intended to provide a treatment of the theory and applications of Stochastic Neural Networks,that is networks able to learn;

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Principles Of Artificial Neural Networks

The field of Artificial Neural Networks is the fastest growing field in Information Technology and specifically, in Artificial Intelligence;

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Information-Theoretic Aspects of Neural Networks

Information theoretics vis-a-vis neural networks generally embodies parametric entities and conceptual bases pertinent to memory;

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Brain Theory and Neural Networks

it will provide in-depth knowledge about the theory and practice of brain theory and neural networks. With state-of-the-art inputs by;

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Mathematical Perspectives on Neural Networks

mathematics, and address questions such as: * Exactly what mathematical systems are used to model neural networks from the given perspective;

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Mathematical Perspectives on Neural Networks

mathematics, and address questions such as: * Exactly what mathematical systems are used to model neural networks from the given perspective;

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Quantum Computing

are integrated from statistical physics, information theory, and computer science. Statistical neural field theory and the AdS/CFT;

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Connectionist Representations of Tonal Music

Previously, artificial neural networks have been used to capture only the informal properties of music. However, cognitive scientist;

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Complex-valued Neural Networks

-ever book on complex-valued neural networks, the most active scientists at the forefront of the field describe theories and applications from;

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Power Converters and Ac Electrical Drives With Linear Neural Networks

of neural networks in the field of power electronics, with particular emphasis on the sensorless control of AC drives. It presents the classical;

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Theory and Applications of Neural Networks

Grossberg was a guest speaker on the first day giving a thorough introduction to his Adaptive Resonance Theory of neural networks. Subsequent;

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Artificial Neural Networks - ICANN 2009

of learning by example. The field of artificial neural networks has evolved significantly in the last two decades, with active partici- tion from;

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Simulating Neural Networks with Mathematica

application programs ( packages ) in Appendix. (Also available electronically from MathSource.) Table of ContentsIntroduction to Neural Networks and;

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Power Converters And Ac Electrical Drives With Linear Neural

of neural networks in the field of power electronics, with particular emphasis on the sensorless control of AC drives. It presents the classical;

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Kinematic Control of Redundant Robot Arms Using Neural Networks

presents and investigates different methods and schemes for the control of robotic arms whilst exploring the field from all angles. On a more;

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Statistical Learning Using Neural Networks

in data mining and artificial intelligence (AI). This book brings together data analysis from statistics to computer science using neural networks.;

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Statistical Learning Using Neural Networks

in data mining and artificial intelligence (AI). This book brings together data analysis from statistics to computer science using neural networks.;

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Progress in Neural Networks V 6

, and development of neural networks in software and hardware areas. The book includes contributions from leading researchers, serving as a;

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Spatially Explicit Hyperparameter Optimization for Neural Networks

automated spatially explicit hyperparameter optimization approach to identify optimal or near-optimal parameter settings for neural networks in the;

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Deep Neural Networks in a Mathematical Framework

to represent and describe neural networks, casting previous results in the field in a more natural light. In particular, the authors derive;

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World Congress on Neural Networks

registrants -- from a diverse background encompassing industry, academia, and government -- with the latest research and applications in the neural;

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Circuit Complexity and Neural Networks

that will enable neural network scientists to learn about how complexity theory applies to their discipline, and allow complexity theorists to;

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Neural Networks and Analog Computation: Beyond the Turing Limit

networks, adaptive engineering tools, and related models from the fields of control theory and nonlinear dynamics. The material in this book will;

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Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management

provides comprehensive coverage of the most important materials relating to the applications of ANNs in the cancer field. With contributions from;

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Static and Dynamic Neural Networks

Provides comprehensive treatment of the theory of both static and dynamic neural networks. Theoretical concepts are illustrated by;

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