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Adaptive Neural Control of Walking Robots

of technological development: adaptive neural control and mobile/walking robots. The development and management of locomotory robots has not only produced;

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Neural and Adaptive Systems

engineering, it unifies the concepts of neural networks and adaptive filters into a common framework. It begins by explaining the fundamentals;

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Neural Network Perspectives on Cognition and Adaptive Robotics

Featuring an international team of authors, Neural Network Perspectives on Cognition and Adaptive Robotics presents several approaches to;

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Neural Network Perspectives on Cognition and Adaptive Robotics

Featuring an international team of authors, Neural Network Perspectives on Cognition and Adaptive Robotics presents several approaches to;

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

concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural;

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Neural Network-Based Adaptive Control of Uncertain Nonlinear Systems

network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control;

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Adaptive Sliding Mode Neural Network Control for Nonlinear Systems

Adaptive Sliding Mode Neural Network Control for Nonlinear Systems introduces nonlinear systems basic knowledge, analysis and control;

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Robust Adaptive Control for Fractional-Order Systems with Disturbance and Saturation

A treatise on investigating tracking control and synchronization control of fractional-order nonlinear systems with system uncertainties;

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Print Proceedings of the ASME 2015 Dynamic Systems and Control Conference (DSCC2015)

Assistive Robotics Biomed and Neural Systems;

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Neural Network Control of Nonlinear Discrete-Time Systems

neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control;

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Adaptive Business Intelligence

. Coverage includes linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy;

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Adaptive Business Intelligence

. Coverage includes linear regression, time-series forecasting, decision trees and tables, artificial neural networks, genetic programming, fuzzy;

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Artificial Adaptive Systems Using Auto Contractive Maps

used to analyze them. It subsequently describes artificial neural networks as a subclass of artificial adaptive systems, and reports on the;

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Soft Computing with NeuroFuzzy Systems

neuro-fuzzy inference system for optimal design of reinforced concrete beams; comparison between neural network and adaptive neuro-fuzzy;

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Deep Reinforcement Learning with Guaranteed Performance

control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the;

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Neural Network Modeling and Identification of Dynamical Systems

Neural Network Modeling and Identification of Dynamical Systems presents a new approach on how to obtain the adaptive neural network;

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Applications of Neural Networks in High Assurance Systems

Applications of Neural Networks in High Assurance Systems is the first book directly addressing a key part of neural network technology;

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Intelligent and Adaptive Systems in Medicine

using intelligent and adaptive systems. The book focuses on the methods of fuzzy logic, artificial neural networks, neuro-fuzzy modeling;

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Intelligent and Adaptive Systems in Medicine

using intelligent and adaptive systems. The book focuses on the methods of fuzzy logic, artificial neural networks, neuro-fuzzy modeling;

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Print Proceedings of the ASME 2017 10th Annual Dynamic Systems and Control Conference (DSCC2017)

; Bio-Mechatronics and Physical Human Robot; Biomedical and Neural Systems Modeling, Diagnostics, and Control.;

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Adaptive Control

sliding mode control for under-actuated mechanical systems; neural network adaptive PID control design based on PLC for a water-level system; and;

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Deep Neuro-Fuzzy Systems with Python

Gain insight into fuzzy logic and neural networks, and how the integration between the two models makes intelligent systems in the current;

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Intelligent Signal Processing

Signal Processing explores how ISP tools address the problems of practical neural systems, new signal data, and blind fuzzy approximators. The;

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Neural Network Control Of Robots And Nonlinear Systems

. The first chapter provides a background on neural networks and the second on dynamical systems and control. Chapter three introduces the robot;

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System Identification and Adaptive Control

concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control;

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Adaptive Wireless Transceivers

modulation mode switching and highlights a range of practical considerations. Introduces neural network based channel equalisers and discusses;

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Cooperative Control Of Multi-Agent Systems

cooperative control is introduced and neural adaptive design techniques for multi-agent nonlinear systems with unknown dynamics, which are rarely;

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