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The Essence of Neural Networks

The Essence of Neural Networks 1e editie is een boek van Robert Callan uitgegeven bij Pearson Education (Us). ISBN 9780139087325

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New Developments In Artificial Neural Networks Research

This book gathers the most current research from across the globe in the study of artificial neural networks. Topics discussed include a;

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Focus on Artificial Neural Networks

This book gathers the most current research from across the globe in the study of artificial neural networks. Topics discussed include;

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Neural Networks for Complete Beginners

This book is an exploration of an artificial neural network. It has been created to suit even the complete beginners to artificial neural;

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Complex-valued Neural Networks

-Dimensional Parameters covers the current state-of-the-art theories and applications of neural networks with high-dimensional parameters such as;

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Evolutionary Machine Learning Techniques

networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions, literature reviews;

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Evolutionary Machine Learning Techniques

networks, modular neural networks, physical neural networks, and deep neural networks. The book provides essential definitions;

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Kinematic Control of Redundant Robot Arms Using Neural Networks

specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations;

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Applied Neural Networks and Soft Computing

Applied Neural Networks and Soft Computing examines the relation between neural networks and soft computing. Neural network is a system;

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Information-Theoretic Aspects of Neural Networks

sparsely cover the entropy and/or cybernetic aspects of neural information. Information-Theoretic Aspects of Neural Networks cohesively explores;

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Complex-Valued Neural Networks

This book covers the hot topics and applications surrounding complex-valued neural networks. It demonstrates advanced theories with a wide;

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Neural Networks with R

Uncover the power of artificial neural networks by implementing them through R code. About This Book * Develop a strong background;

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Neural Network Programming with Java

This book is an exploration of neural networks and how to implement them in Java. First, the reader is guided so as to understand what;

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Neural Information Processing

The seven-volume set of LNCS 11301-11307, constitutes the proceedings of the 25th International Conference on Neural Information Processing;

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Spatially Explicit Hyperparameter Optimization for Neural Networks

Neural networks as the commonly used machine learning algorithms, such as artificial neural networks (ANNs) and convolutional neural;

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Simulating Neural Networks with Mathematica

This book introduces neural networks, their operation, and application, in the context of the interactive Mathematica environment. Readers;

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Computational Mechanics with Neural Networks

This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other;

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Computational Mechanics with Neural Networks

This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other;

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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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Complex-valued Neural Networks

In recent years, complex-valued neural networks have widened the scope of application in optoelectronics, imaging, remote sensing, quantum;

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Neural Network Programming with Python

This book is a guide on how to implement a neural network in the Python programming language. It begins by giving you a brief overview;

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Deep Learning from Scratch Building with Python from First Principles

With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many;

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Blind Equalization in Neural Networks

The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms;

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Introduction to Neural Networks for Java, Second Edition

"Introduction to Neural Networks for Java" introduces the Java programmer to the world of Neural Networks and Artificial Intelligence;

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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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Circuit Complexity and Neural Networks

amounts of input data. Circuit Complexity and Neural Networks addresses the important question of how well neural networks scale - that is, how;

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Exploring Neural Networks with C#

The utility of artificial neural network models lies in the fact that they can be used to infer functions from observations-making them;

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