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Cellular Neural Networks, Multi-scroll Chaos And Synchronization

. Cellular neural networks and their universal machine implementations offer a well-established platform for processing spatial-temporal patterns and;

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Neural Information Processing

Neural Information Processing, ICONIP 2019, held in Sydney, Australia, in December 2019.For ICONIP 2019 a total of 345 papers was carefully;

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

applications This book focuses on how to build energy-efficient hardware for neural networks with learning capabilities-and provides co-design and;

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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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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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Temporal Self-organization for Neural Networks

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Temporal Self-organization for Neural Networks

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Recurrent Neural Networks for Temporal Data Processing

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Computational Intelligence

systems and evolutionary neural systems. Applications to linear and non-linear systems are discussed with examples. Key features: * Covers all;

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Type 2 Fuzzy Neural Networks and Their Applications

This book deals with the theory, design principles, and application of hybrid intelligent systems using type-2 fuzzy sets in combination;

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Neural Network Analysis, Architectures and Applications

Neural Network Analysis, Architectures and Applications discusses the main areas of neural networks, with each authoritative chapter;

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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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Networks & Quantum Computing

This book presents and discusses research in the field of computer science, with a particular focus on network systems and quantum;

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The Relevance of the Time Domain to Neural Network Models

time domain can be effectively employed in neural network models. A first direction to consider is to deploy oscillators that model temporal;

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Neural Networks for Robotics

The book offers an insight on artificial neural networks for giving a robot a high level of autonomous tasks, such as navigation, cost;

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Neural Networks for Robotics

The book offers an insight on artificial neural networks for giving a robot a high level of autonomous tasks, such as navigation, cost;

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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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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

. The chapters start with the design of a new fuzzy-neural controller. Remaining chapters discuss the application of expert systems, neural;

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Neural Networks

With respect to the ever-increasing developments in artificial intelligence and artificial neural network applications in different scopes;

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Organic Computing

In this book, the major ideas behind Organic Computing are delineated, together with a sparse sample of computational projects undertaken;

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Organic Computing

In this book, the major ideas behind Organic Computing are delineated, together with a sparse sample of computational projects undertaken;

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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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Quantum Computing

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

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Applications of Soft Computing in Time Series Forecasting

book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization;

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Applications of Soft Computing in Time Series Forecasting

book describes novel methods resulting from the hybridization of FTS modeling approaches with neural networks and particle swarm optimization;

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Sensory Neural Networks

book also uses nonlinear mathematical techniques to analyze temporal and spatial behavior of models presented within the text. Sensory Neural;

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Revival: Sensory Neural Networks (1991)

book also uses nonlinear mathematical techniques to analyze temporal and spatial behavior of models presented within the text. Sensory Neural;

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