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Blind Equalization in Neural Networks

The book begins with an introduction of blind equalization theory and its application in neural networks, then discusses the algorithms;

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Wavelet Neural Networks

chaotic time series prediction An extensive introduction to neural networks that begins with regression models and builds to more complex;

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Neural Networks for Optimization and Signal Processing

A topical introduction on the ability of artificial neural networks to not only solve on-line a wide range of optimization problems but;

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Fundamentals Neural NetworksUnited State

An exceptionally clear, thorough introduction to neural networks written at an elementary level. Written with the beginning student in mind;

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Computational Neuroscience

references. The first book to bring you cutting-edge developments in neuronal modeling. It provides an introduction to realistic modeling methods;

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Artificial Neural Networks

Artificial neural networks are graphical structures whose initial purpose was to emulate the human brain. They were introduced in 1943 by;

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An Introduction to the Modeling of Neural Networks

This text is a beginning graduate-level introduction to neural networks, focussing on current theoretical models, examining what these;

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Introduction to Neural Networks for Java, Second Edition

"Introduction to Neural Networks for Java" introduces the Java programmer to the world of Neural Networks and Artificial Intelligence;

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Gas Turbines Modeling, Simulation, and Control

Gas Turbines Modeling, Simulation, and Control: Using Artificial Neural Networks provides new approaches and novel solutions to the;

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Gas Turbines Modeling, Simulation, and Control

Gas Turbines Modeling, Simulation, and Control: Using Artificial Neural Networks provides new approaches and novel solutions to the;

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Modeling Neural Development

An important collection showing how computational and mathematical modeling can be used to study the complexities of neural development;

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Applications of Soft Computing in Time Series Forecasting

modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and;

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Applications of Soft Computing in Time Series Forecasting

modeling and also provides a brief introduction to other soft-computing techniques, such as artificial neural networks (ANNs), rough sets (RS) and;

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Introduction to Graph Neural Networks

comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with the introduction of the vanilla GNN;

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Introduction to Graph Neural Networks

This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with;

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Neural Networks Modeling and Control

neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on;

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Building Neural Networks

This practical introduction describes the kinds of real-world problems neural network technology can solve. Surveying a range of neural;

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Introduction to Neural and Cognitive Modeling

This textbook provides a general introduction to the field of neural networks. Thoroughly revised and updated from the previous editions;

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Introduction to Neural and Cognitive Modeling

This textbook provides a general introduction to the field of neural networks. Thoroughly revised and updated from the previous editions;

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Introduction to Deep Learning and Neural Networks with PythonT

Introduction to Deep Learning and Neural Networks with PythonT: A Practical Guide is an intensive step-by-step guide for neuroscientists to;

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A Comprehensive Guide to Neural Network Modeling

As artificial neural networks have been gaining importance in the field of engineering, this compilation aims to review the scientific;

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Engineering Applications of Neural Networks

This book constitutes the refereed proceedings of the 16th International Conference on Engineering Applications of Neural Networks, EANN;

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Artificial Neural Networks in Food Processing

comprehensive overview of ANNs including an introduction to the topic, classifications of single neurons and neural networks, model predictive control;

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Modeling of Thermodynamic Properties of Refrigerants Using Artifical Neural Networks & Genetic Algorithm

, involving the solution of complex differential equations. This book provides an alternative simple approach based on artificial neural networks;

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Brain Dynamics

This is an excellent introduction for graduate students and nonspecialists to the field of mathematical and computational neurosciences;

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Brain Dynamics

This is an excellent introduction for graduate students and nonspecialists to the field of mathematical and computational neurosciences;

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Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools

learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.;

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