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Neural Networks for Applied Sciences and Engineering

In response to the exponentially increasing need to analyze vast amounts of data, Neural Networks for Applied Sciences and Engineering;

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Neural Networks and Analog Computation: Beyond the Turing Limit

be of interest to researchers in a variety of engineering and applied sciences disciplines. In addition, the work may provide the base of a;

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Focus on Artificial Neural Networks

artificial neural networks in environmental sciences and chemical engineering; application of artificial neural networks in the development;

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Artificial Neural Networks for Engineers and Scientists

equations, and these methods are presented in Artificial Neural Networks for Engineers and Scientists: Solving Ordinary Differential Equations. This;

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Artificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that;

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Applied Neural Networks for Signal Processing

principles and models of neural networks in signal processing. The authors then discuss a number of powerful algorithms and architectures for a range;

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A Comprehensive Guide to Neural Network Modeling

literature regarding the use of artificial neural networks for the modelling and optimization of food drying processes. The applications;

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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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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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Wavelet Neural Networks

constructing confidence and prediction intervals Ideal as a textbook for MBA and graduate-level courses in applied neural network modeling, artificial;

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Proceedings of the 21st EANN (Engineering Applications of Neural Networks) 2020 Conference

includes robust algorithmic approaches and applications in a broad spectrum of scientific fields, namely the use of convolutional neural networks;

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Kinematic Control of Redundant Robot Arms Using Neural Networks

Networks for Parallel Robot Control; and Neural Networks for Cooperative Control. The book starts by covering zeroing neural networks for control;

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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

basis for representing uncertain and imprecise knowledge and forms a basis for human reasoning. Neural networks display genuine promise;

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Learning from Data

An interdisciplinary framework for learning methodologies-covering statistics, neural networks, and fuzzy logic, this book provides a;

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Stability Analysis and State Estimation of Memristive Neural Networks

In this book, the stability analysis and estimator design problems are discussed for delayed discrete-time memristive neural networks;

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Neural Networks And Artificial Intelligence For Biomedical Engineering

biomedicine based on current theory and applications of neural networks, artificial intelligence, and other methods for the development of decision;

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Fuzzy Neural Intelligent Systems

of the theories, algorithms, and designs of systems for specific applications. There has been little theoretical support for fuzzy neural systems;

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Neural Control Engineering

control engineering in the late 1990s has made the intersection of control theory and neuroscience possible. In Neural Control Engineering, Steven;

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Artificial Neural Networks - ICANN 2009

neuroscience. Artificial neural networks have been widely applied for pattern recognition, control, optimization, image processing, classification;

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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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Simulating Neural Networks with Mathematica

will learn how to simulate neural network operations using Mathematica, and will learn techniques for employing Mathematica to assess neural;

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Artificial Neural Networks

This volume presents examples of how Artificial Neural Networks (ANNs) are applied in biological sciences and related areas. Chapters cover;

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Zeroing Dynamics, Gradient Dynamics, and Newton Iterations

Neural networks and neural dynamics are powerful approaches for the online solution of mathematical problems arising in many areas;

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Designs and Applied Principles of Artificial Neural Networks

This book presents a broad overview on the current various design modules and applications of artificial neural systems. Artificial neural;

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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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Deep Learning for Data Analytics

analyze large volumes of data for business, engineering, and biomedical applications. Deep learning architectures including deep neural networks;

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