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The Neural Control of Movement

underlying how this important behavior occurs. The Neural Control of Movement discusses these developments across a variety of species;

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Kinematic Control of Redundant Robot Arms Using Neural Networks

specific level, it deals with the dynamic-neural-network based kinematic control of redundant robot arms by using theoretical tools and simulations;

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Three-dimensional Kinematics of the Eye, Head and Limb Movements

, to describe the laws of human movement and to deduce the neural control principles underlying these laws. After long neglect - partly due to;

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Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to;

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Advanced Rehabilitative Technology

musculoskeletal models and establish the neural interfaces, and how to develop neural devices and control them efficiently using biological signals. The;

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Motor Control Concepts and Issues

Motor Control: Concepts and Issues D.R. Humphrey H.-J. Freund Editors Studies of the neural control of movement and posture have come to be;

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Adaptive Neural Control of Walking Robots

An important title in the Engineering Research Series Adaptive Neural Control of Walking Robots brings together two important areas;

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Neural Networks Modeling and Control

two methodologies: sliding mode control and Inverse Optimal Neural Control. As well as considering the different neural control;

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Robot Control using an Artificial Neural Network

modifications to the neural network used19 3.5Learning capacity22 4.Teaching and control techniques23 5.The software28 5.1The te";

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Peripheral and Spinal Mechanisms in the Neural Control of Movement

activity and movement. Paradoxically, a host of new findings have revealed an unexpected versatility in the behavior of these well-studied neural;

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Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems

historical overview of adaptive control, followed by a review of mathematical preliminaries. In the subsequent chapters, they present several neural;

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Stability and Synchronization Control of Stochastic Neural Networks

synchronization control. The book will be of interest to university researchers, graduate students in control science and engineering and neural networks;

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Stability and Synchronization Control of Stochastic Neural Networks

synchronization control. The book will be of interest to university researchers, graduate students in control science and engineering and neural networks;

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Qualitative Analysis and Control of Complex Neural Networks with Delays

This book focuses on the stability of the dynamical neural system, synchronization of the coupling neural system and their applications;

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Neural Network Control of Nonlinear Discrete-Time Systems

. Progressive Development After an introduction to neural networks, dynamical systems, control of nonlinear systems, and feedback linearization, the;

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Neural Networks for Cooperative Control of Multiple Robot Arms

is intended for graduate students and academic and industrial researchers in the field of control, robotics, neural networks, simulation and modelling.;

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Power Converters and Ac Electrical Drives With Linear Neural Networks

of neural networks in the field of power electronics, with particular emphasis on the sensorless control of AC drives. It presents the classical;

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Power Converters And Ac Electrical Drives With Linear Neural

of neural networks in the field of power electronics, with particular emphasis on the sensorless control of AC drives. It presents the classical;

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Neural Networks for Control

capabilities of neural network controllers. The appendix describes seven benchmark control problems. Contributors Andrew G. Barto, Ronald J. Williams;

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Fusion of Neural Networks, Fuzzy Systems and Genetic Algorithms

Artificial neural networks can mimic the biological information-processing mechanism in - a very limited sense. Fuzzy logic provides a;

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Artificial Neural Networks

. aircraft motion control). This edition contains relevant, state-of-the-art research on artificial neural networks, categorized in four sections;

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Discrete-Time Recurrent Neural Control

The book presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple;

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Discrete-Time Recurrent Neural Control

The book presents recent advances in the theory of neural control for discrete-time nonlinear systems with multiple inputs and multiple;

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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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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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Network Models for Control and Processing

related fields. These cover: control processes, modelling features and operations of biological neural networks and neurons, simulation;

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A First Course in Fuzzy and Neural Control

given situation. A First Course in Fuzzy and Neural Control is designed to build the foundation needed to make those decisions. It begins;

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