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Cellular Neural Networks, Multi-scroll Chaos And Synchronization

design principles. This perspective is the basis of the three cornerstones of this book: cellular neural networks, chaos and synchronization;

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Handbook on Neural Information Processing

applications. The contributions include: Deep architectures Recurrent, recursive, and graph neural networks Cellular neural networks Bayesian networks;

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Neural Network Analysis, Architectures and Applications

simplifying networks. It then describes novel architectures and algorithms, including pulse-stream techniques, cellular neural networks, and;

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Information-Theoretic Aspects of Neural Networks

-theoretic transfer function of the neural cellular units statistical mechanics, neural networks, and information theory semiotic framework;

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Cellular Neural Networks

Cellular Neural Networks (CNN's) were introduced in 1988 by L O Chua and L Yang as a novel class of information processing systems, which;

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Artificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that;

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Chaos & Complexity

This book presents new international research on artificial life, cellular automata, chaos theory, cognition, complexity theory;

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Chaos & Complexity

This book presents new international research on artificial life, cellular automata, chaos theory, cognition, complexity theory;

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Chaos & Complexity Research Compendium

This book presents leading-edge research on artificial life, cellular automata, chaos theory, cognition, complexity theory, synchronisation;

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Cellular Neural Networks and Visual Computing

Cellular Nonlinearneural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm;

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Cellular Neural Networks and Visual Computing

Cellular Nonlinearneural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm;

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Progress in Chaos Complexity Research

This book presents new leading-edge research on artificial life, cellular automata, chaos theory, cognition, complexity theory;

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Chaos & Complexity Research Compendium

This book presents leading-edge research on artificial life, cellular automata, chaos theory, cognition, complexity theory, synchronisation;

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Chaos & Complexity Reasearch Compendium

This book presents leading-edge research on artificial life, cellular automata, chaos theory, cognition, complexity theory, synchronisation;

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Reconfigurable Cellular Neural Networks and Their Applications

to the cellular neural network (CNN) and formulates it to match the behavior of the Wilson-Cowan model. In turn, two properties that are;

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Chaos, CNN, Memristors and Beyond

neural networks, and chaos. It is comprised of three parts. The first - cellular nonlinear networks, nonlinear circuits and cellular automata;

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New Research on Chaos & Complexity

This book presents leading-edge research on artificial life, cellular automata, chaos theory, cognition, complexity theory, synchronisation;

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Developments in Chaos & Complexity Research

This book presents the latest leading-edge international research on artificial life, cellular automata, chaos theory, cognition;

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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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Unconventional Computation and Natural Computation

computing; physarum computing; computation in hyperbolic spaces; collision-based computing; cellular automata; neural computation; evolutionary;

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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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