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Principal Component Neural Networks

Systematically explores the relationship between principal component analysis (PCA) and neural networks. Provides a synergistic examination;

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Statistics and Neural Networks

principal component analysis, density networks and the use of multiple latent variables; and a substantial chapter outlining techniques and their;

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Principal Component Analysis Networks and Algorithms

This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA;

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Machine Learning for Future Fiber-Optic Communication Systems

-maximization (EM) algorithm, principal component analysis (PCA), independent component analysis (ICA), reinforcement learning, and more Covers;

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Neural Networks For Pattern Recognition

This book provides the first comprehensive treatment of feed-forward neural networks from the perspective of statistical pattern;

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Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference

This book gathers the proceedings of the 21st Engineering Applications of Neural Networks Conference, which is supported by the;

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Complex-Valued Neural Networks

This book is the second enlarged and revised edition of the first successful monograph on complex-valued neural networks (CVNNs) published;

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Applications of Neural Networks in High Assurance Systems

Applications of Neural Networks in High Assurance Systems is the first book directly addressing a key part of neural network technology;

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Neural Networks and Statistical Learning

radial basis function network; * recurrent neural networks; * nonnegative matrix factorization; * independent component analysis;

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Face Recognition

control systems. Topics discussed in this compilation include two-dimensional principal component analysis algorithms for face recognition;

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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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Kinematic Control of Redundant Robot Arms Using Neural Networks

Presents pioneering and comprehensive work on engaging movement in robotic arms, with a specific focus on neural networks This book;

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Complex-valued Neural Networks

Recent research indicates that complex-valued neural networks whose parameters (weights and threshold values) are all complex numbers are;

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Evolutionary Machine Learning Techniques

machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic;

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Evolutionary Machine Learning Techniques

machines, evolutionary feature selection, artificial neural networks including feed-forward neural networks, multi-layer perceptron, probabilistic;

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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

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

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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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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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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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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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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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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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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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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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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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