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Statistical Mechanics of Neural Networks

chaos theory of recurrent neural networks, and eigen-spectrums of neural networks, walking new learners through the theories and must-have;

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Advanced Models of Neural Networks

with neural networks and dynamical systems theory.;

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Neural Networks Theory

This book, written by a leader in neural network theory in Russia, uses mathematical methods in combination with complexity theory;

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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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Information-Theoretic Aspects of Neural Networks

-theoretic transfer function of the neural cellular units statistical mechanics, neural networks, and information theory semiotic framework;

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Circuit Complexity and Neural Networks

network learning. Circuit Complexity and Neural Networks contains a significant amount of background material on conventional complexity theory;

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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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Simulating Neural Networks with Mathematica

with Neural Networks Feedback and Recurrent Networks Adaptive Resonance Theory Genetic Algorithms 020156629XB04062001;

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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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Principles Of Artificial Neural Networks

and Machine Learning.This must-have compendium presents the theory and case studies of artificial neural networks. The volume, with 4 new;

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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 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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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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Static and Dynamic Neural Networks

Provides comprehensive treatment of the theory of both static and dynamic neural networks. Theoretical concepts are illustrated by;

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Mathematical Aspects of Spin Glasses and Neural Networks

Aimed at graduates and potential researchers, this is a comprehensive introduction to the mathematical aspects of spin glasses and neural;

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Mathematical Aspects of Spin Glasses and Neural Networks

Aimed at graduates and potential researchers, this is a comprehensive introduction to the mathematical aspects of spin glasses and neural;

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New Developments In Artificial Neural Networks Research

This book gathers the most current research from across the globe in the study of artificial neural networks. Topics discussed include a;

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Neural Networks and Animal Behavior

important question by applying neural network theory. Scientists create Artificial Neural Networks (ANNs) to make models of the brain. These;

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Neural Networks And Their Applications

Neural networks are one of the fast-growing paradigms for learning systems with a wide variety of potential applications in industry;

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Deep Learning and Practice with MindSpore

This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore;

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Deep Learning and Practice with MindSpore

This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore;

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Nonlinear Dynamical Systems

The first truly up-to-date look at the theory and capabilities of nonlinear dynamical systems that take the form of feedforward neural;

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Neural Networks and Qualitative Physics

physics. Professor Aubin makes use of control and viability theory in neural networks and cognitive systems, regarded as dynamical systems;

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Neural Networks And Qualitative Physics

physics. Professor Aubin makes use of control and viability theory in neural networks and cognitive systems, regarded as dynamical systems;

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Focus on Artificial Neural Networks

This book gathers the most current research from across the globe in the study of artificial neural networks. Topics discussed include;

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