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Complex-Valued Neural Networks with Multi-Valued Neurons

Complex-Valued Neural Networks have higher functionality, learn faster and generalize better than their real-valued counterparts. This book;

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Supervised Learning with Complex-valued Neural Networks

monograph comprises a collection of new supervised learning algorithms along with novel architectures for complex-valued neural networks. The;

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Complex-valued Neural Networks

In recent years, complex-valued neural networks have widened the scope of application in optoelectronics, imaging, remote sensing, quantum;

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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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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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Complex-Valued Neural Networks

that deal with complex numbers? What advantages do the complex-valued neural networks have? What is the origin of the advantages? In what areas;

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Neural Networks

Neural networks are used to model complex patterns for prediction and simulation. It uses the processing pattern used by brain neurons to;

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Neural Networks

Neural networks are used to model complex patterns for prediction and simulation. It uses the processing pattern used by brain neurons to;

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Real-Time Multi-Chip Neural Network for Cognitive Systems

neurons process information and communicate with each other, in effect efficiently complementing in-vivo experiments. In spiking neural networks;

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Neural Networks and Qualitative Physics

This book is devoted to some mathematical methods that arise in two domains of artificial intelligence: neural networks and qualitative;

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Neural Networks And Qualitative Physics

This book is devoted to some mathematical methods that arise in two domains of artificial intelligence: neural networks and qualitative;

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Brain Theory and Neural Networks

it will provide in-depth knowledge about the theory and practice of brain theory and neural networks. With state-of-the-art inputs by;

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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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Multi-Valued Variational Inequalities and Inclusions

self-contained exposition of existence, comparison and enclosure principles, together with other qualitative properties of multi-valued;

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Multi-Valued Variational Inequalities and Inclusions

self-contained exposition of existence, comparison and enclosure principles, together with other qualitative properties of multi-valued;

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Decision Making Theories and Methods Based on Interval Valued Intuitionistic Fuz

fuzzy sets, multi-criteria decision-making methods with interval-valued intuitionistic fuzzy sets, and group decision-making methods with;

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Neural Networks for Applied Sciences and Engineering

: From Fundamentals to Complex Pattern Recognition provides scientists with a simple but systematic introduction to neural networks;

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Neural Networks with R

with knowledge in R and wants to work with neural networks to get better results from complex data. If you are interested in artificial;

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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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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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Artificial Neural Network Modeling of Water & Wastewater Treatments Processes

Artificial neural networks (ANNs) are computer based systems that are designed to simulate the learning process of neurons in the human;

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Artificial Neural Networks

. Section 1 focuses on Biological neural networks, describing: spike activity prediction based on multi-neuron spike train data, neuromorphic;

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Circuit Complexity and Neural Networks

Neural networks usually work adequately on small problems but can run into trouble when they are scaled up to problems involving large;

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Decision Making Theories and Methods Based on Inte

intuitionistic fuzzy sets, multi-criteria decision-making methods with interval-valued intuitionistic fuzzy sets, and group decision-making methods with;

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J-Contractive Matrix Valued Functions and Related Topics

geometry of finite dimensional spaces with an indefinite inner product, and the theory of the Nevanlinna class of matrix valued functions with;

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Set-Valued Stochastic Integrals and Applications

well as the first to contain complex approach theory of set-valued stochastic integrals. Taking particular consideration of set-valued Ito;

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Set-Valued Stochastic Integrals and Applications

well as the first to contain complex approach theory of set-valued stochastic integrals. Taking particular consideration of set-valued Ito;

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