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Computational Mechanics with Neural Networks

This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other;

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Computational Mechanics with Neural Networks

This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other;

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Combinatorial and Computational Mathematics

, Neural Networks, Computational Methods in Fluid Mechanics and Formal Languages provide applications of well-known areas like Computational Fluid;

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Deep Learning in Computational Mechanics

This book provides a first course on deep learning in computational mechanics. The book starts with a short introduction to machine;

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Deep Learning in Computational Mechanics

This book provides a first course on deep learning in computational mechanics. The book starts with a short introduction to machine;

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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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Neural Networks and Analog Computation: Beyond the Turing Limit

treatment of neural computations enriches the theory of computation but also explicated the computational complexity associated with biological;

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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 Neural Networks in Biological and Environmental Analysis

fundamental, technological, and applied aspects of computational neural networks. Presenting the basic principles of neural networks together with;

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Artificial Neural Networks in Biological and Environmental Analysis

fundamental, technological, and applied aspects of computational neural networks. Presenting the basic principles of neural networks together with;

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Neural Networks with R

in neural networks with R, to implement them in your applications * Build smart systems using the power of deep learning * Real-world case studies;

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Supervised and Unsupervised Pattern Recognition

There are many books on neural networks, some of which cover computational intelligence, but none that incorporate both feature extraction;

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Mathematical Perspectives on Neural Networks

. Mathematical models of neural networks display an amazing richness and diversity. Neural networks can be formally modeled as computational systems, as;

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Mathematical Perspectives on Neural Networks

. Mathematical models of neural networks display an amazing richness and diversity. Neural networks can be formally modeled as computational systems, as;

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Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

of computation of neural networks uncertainty with robust parameter estimation are presented. Moreover, a novel approach for system identification with;

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Network Models for Control and Processing

experimentation and physical mechanisms with computer-assisted and hardware models of biological neural networks and neurons; improving processes for;

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Neural Network Learning

learning problems, and addresses the key statistical and computational questions. Research on pattern classification with binary-output networks;

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Neural Network Learning

learning problems, and addresses the key statistical and computational questions. Research on pattern classification with binary-output networks;

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Artificial Neural Networks in Food Processing

Artificial Neural Networks (ANNs) is a powerful computational tool to mimic the learning process of the mammalian brain. This book gives a;

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Computational Modelling of Objects Represented in Images III

with multidisciplinary interests related to Computational Vision, Computational Mechanics, Medicine, Engineering and Architecture.;

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Artificial Neural Networks - ICANN 2009

), in cooperation with the - ternational Neural Network Society (INNS) and the Japanese Neural Network Society (JNNS). ICANN 2009 was technically sponsored;

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Fundamentals of Computational Intelligence

covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary;

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Computational Architectures Integrating Neural and Symbolic Processes

Computational Architectures Integrating Neural and Symbolic Processes: A Perspective on the State of the Art focuses on a currently;

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Advances in Computational Intelligence

Neural Networks, IWANN 2019, held at Gran Canaria, Spain, in June 2019. The 150 revised full papers presented in this two-volume set were;

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Advances in Computational Intelligence

Neural Networks, IWANN 2019, held at Gran Canaria, Spain, in June 2019. The 150 revised full papers presented in this two-volume set were;

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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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