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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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Unconventional Computation and Natural Computation

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

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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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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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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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Convolutional Neural Networks in Visual Computing

This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's;

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Convolutional Neural Networks in Visual Computing

This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's;

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Neural Information Processing

follows: adversarial networks and learning; convolutional neural networks; deep neural networks; embeddings and feature fusion; human centred;

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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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Learning in Energy-Efficient Neuromorphic Computing - Algorithm and Architecture Co-Design

Explains current co-design and co-optimization methodologies for building hardware neural networks and algorithms for machine learning;

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Neural Information Processing

The three-volume set of LNCS 11953, 11954, and 11955 constitutes the proceedings of the 26th International Conference on Neural Information;

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New Developments In Artificial Neural Networks Research

neural network based visual servo system; modelling of computer-assisted learning using artificial neural networks; prediction of hole quality;

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Computational Intelligence

Computational Intelligence: Synergies of Fuzzy Logic, Neural Networks and Evolutionary Computing presents an introduction to some of the;

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Type 2 Fuzzy Neural Networks and Their Applications

of the foundation of type-2 fuzzy neural networks and presents a vast compendium of its applications to control, forecasting, decision making;

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Artificial Intelligence in the Age of Neural Networks and Brain Computing

Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that existing disruptive implications and;

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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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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise;

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Networks & Quantum Computing

networks and zeta functions; artificial neural networks for learning; quantum computation and quantum games; decomposition of general quantum gates;

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Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation

applied in two levels. The techniques used and combined in the proposed method are modular neural networks (MNNs) with a Granular Computing (GrC;

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Computational Vision and Bio Inspired Computing

algorithms and results are produced and described. Additionally, this volume addresses evolutionary computation paradigms, artificial neural networks;

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Unconventional Computation and Natural Computation

; cellular automata; neural and evolutionary computation; artificial immune systems; Ant algorithms and swarm intelligence; amorphous computing;

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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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Cognitive Computing: Theory and Applications

, machine learning models and algorithms, biometrics, Kernel Based Models for transductive learning, neural networks, graph analytics in cyber;

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Organic Computing

in this new field. Biological metaphors include evolution, neural networks, gene-regulatory networks, networks of brain modules, hormone system;

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Organic Computing

in this new field. Biological metaphors include evolution, neural networks, gene-regulatory networks, networks of brain modules, hormone system;

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