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Neural Information Processing

networks, recurrent neural networks, and spiking neural networks.;

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Advances in Neural Networks - ISNN 2016

; intelligent control; clustering, classification, modeling, and forecasting; evolutionary computation; and cognition computation and spiking neural;

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Engineering Applications of Neural Networks

machine, machine learning applications, predictive models, fuzzy and recommender systems, recurrent neural networks, spiking neural networks.;

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Evolutionary Machine Learning Techniques

neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy;

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Evolutionary Machine Learning Techniques

neural networks, self-optimizing neural networks, radial basis function networks, recurrent neural networks, spiking neural networks, neuro-fuzzy;

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

networks is also presented. An examination of fundamental concepts and popular learning algorithms for spiking neural networks follows that, along;

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Neural Information Processing

approaches; social network computing; spiking neuron and related models; text computing using neural techniques; time-series and related models; and;

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Windsnelheidsvoorspelling Ontwerp & Implementatie op basis van Spiking Neural Network

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Advances in Computational Intelligence

Biology; Human Computer Interaction; Image and Signal Processing; Mathematics for Neural Networks; Self-organizing Networks; Spiking Neurons;

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Advances in Computational Intelligence

Biology; Human Computer Interaction; Image and Signal Processing; Mathematics for Neural Networks; Self-organizing Networks; Spiking Neurons;

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Neuromorphic Computing Principles and Organization

medium scale spiking neural networks with learning capabilities. In addition, the book describes in a comprehensive way the organization and how;

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Memristive Devices for Brain-Inspired Computing

Learning, and Spiking Neural Networks reviews the latest in material and devices engineering for optimizing memristive devices beyond storage;

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Implementations and Applications of Machine Learning

rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining;

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Implementations and Applications of Machine Learning

rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining;

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Spiking Neuron Models

the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses;

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Spiking Neural Networks

to its ability to emulate biological neural network signals and its enhanced computational capabilities. Input data arrives into a SNN as;

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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

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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Automated EEG-Based Diagnosis of Neurological Disorders

presentation and advancement of Spiking Neural Networks as the seminal foundation of a more realistic and plausible third generation neural network.;

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Automated EEG-Based Diagnosis of Neurological Disorders

presentation and advancement of Spiking Neural Networks as the seminal foundation of a more realistic and plausible third generation neural network.;

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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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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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