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Advanced Models of Neural Networks

This book provides a complete study on neural structures exhibiting nonlinear and stochastic dynamics, elaborating on neural dynamics by;

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Stochastic Models of Neural Networks

This book is intended to provide a treatment of the theory and applications of Stochastic Neural Networks,that is networks able to learn;

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Stability and Synchronization Control of Stochastic Neural Networks

This book reports on the latest findings in the study of Stochastic Neural Networks (SNN). The book collects the novel model of the;

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Stability and Synchronization Control of Stochastic Neural Networks

This book reports on the latest findings in the study of Stochastic Neural Networks (SNN). The book collects the novel model of the;

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Dynamics and Stochastic Processes

The contributions to this volume review the mathematical description of complex phenomena from both a deterministic and stochastic point;

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Statistical Mechanics of Neural Networks

This book highlights a comprehensive introduction to the fundamental statistical mechanics underneath the inner workings of neural networks;

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Artificial Intelligence for Humans, Volume 3

Neural networks have been a mainstay of artificial intelligence since its earliest days. Now, exciting new technologies such as deep;

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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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Network Models for Control and Processing

related fields. These cover: control processes, modelling features and operations of biological neural networks and neurons, simulation;

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The Essence of Neural Networks

The Essence of Neural Networks 1e editie is een boek van Robert Callan uitgegeven bij Pearson Education (Us). ISBN 9780139087325

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Deep Learning with Python

models. All the key architectures in deep learning are covered, including feedforward networks, convolution neural networks, recurrent neural;

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Deep Learning with Python

deep learning models. All the key architectures in deep learning are covered, including feedforward networks, convolution neural networks;

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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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Neural Network Methods in Natural Language Processing

Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data;

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Neural Network Methods in Natural Language Processing

Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data;

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Information-Theoretic Aspects of Neural Networks

information parameters neural information flow dynamics informatics of neural stochastic resonance Information-Theoretic Aspects of Neural;

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Sensory Neural Networks

Sensory information is detected and transformed by sensory neural networks before reaching higher levels of processing. These networks need;

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Revival: Sensory Neural Networks (1991)

Sensory information is detected and transformed by sensory neural networks before reaching higher levels of processing. These networks need;

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Statistical Learning Using Neural Networks

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;

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Statistical Learning Using Neural Networks

Statistical Learning using Neural Networks: A Guide for Statisticians and Data Scientists with Python introduces artificial neural networks;

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Neural Networks with Discontinuous/Impact Activations

This book presents as its main subject new models in mathematical neuroscience. A wide range of neural networks models with discontinuities;

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Mathematical Perspectives on Neural Networks

Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests;

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Mathematical Perspectives on Neural Networks

Recent years have seen an explosion of new mathematical results on learning and processing in neural networks. This body of results rests;

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Recent Advances In Stochastic Modeling And Data Analysis

This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover;

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Neural Networks and Analog Computation: Beyond the Turing Limit

The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer;

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Advanced Deep Learning with Python

Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural;

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Engineering Applications of Neural Networks

This book constitutes the refereed proceedings of the 19th International Conference on Engineering Applications of Neural Networks, EANN;

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