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Neural Network Based Controller for Ups Inverter Applications

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Ultra Wide Band Band Pass Filter

This book provide the Detailed Knowledge of the design of Artificial Neural Network (ANN) based PID controller, to realize fast governor;

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New Developments in Computer Networks

cluster; fuzzy-based controller for improvement of network performance; multi-layer perceptron artificial neural network; fault detection and;

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Neural Fuzzy Control Systems With Structure And Parameter Learning

A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a;

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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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Kinematic Control of Redundant Robot Arms Using Neural Networks

neural network based learning and control co-design for Stewart platform control. The book finishes with a section on zeroing neural networks for;

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Soft Computing with NeuroFuzzy Systems

diagnosis system based on artificial neural network (ANN); reliability estimation of services oriented systems using adaptive neuro fuzzy inference;

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Nonlinear Control Techniques for Robot Manipulators - Nonlinear Control of Mechatronic Systems with Applications in Robotics

redundant robot manipulators, ii) Neural network grasping controller for continuum robots, and iii) Coordination control for haptic and teleoperator;

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Neural Networks Modeling and Control

neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on;

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Artificial Neural Networks

, medical image fusion based on pulse coupled neural networks, artificial neural networks for intrusion detection, recognition of Arabic sign;

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Introduction to the Theory of Neural Computation

Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides;

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Introduction to the Theory of Neural Computation

Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides;

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Computer Science Advances

. Interesting and important topics like fuzzy and cognitive applications, fuzzy classifiers, neural network, data analytics, clustering and;

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Artificial Neural Networks with Java

aspects of using Java for neural network processing. You will know how to use the Encog Java framework for processing large-scale neural network;

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Neural Information Processing

from incomplete data; model compression and optimization; neural network applications; neural network models; semantic and graph based;

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Hardware Architectures for Deep Learning

, and IoT solutions. Efficient implementation of neural networks to support complex deep learning-based applications is a complex challenge for;

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Cyber-Physical Vehicle Systems

. In Chapter 3, an Artificial-Neural-Network-based estimation method is studied for accurate state estimation of CPVS. In Chapter 4, a high-precision;

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Neural Network Analysis, Architectures and Applications

Neural Network Analysis, Architectures and Applications discusses the main areas of neural networks, with each authoritative chapter;

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Artificial Neural Networks with Java

used in neural network development and suggests various techniques of data preparation for many unconventional tasks. The next big topic;

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Artificial Neural Networks with Java

used in neural network development and suggests various techniques of data preparation for many unconventional tasks. The next big topic;

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Neural Network Methods in Natural Language Processing

, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These;

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Neural Network Methods in Natural Language Processing

, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These;

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CAN Made Easy

This book describes the design, implementation and System Verilog simulation of a protocol controller for the Controller Area Network (CAN;

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Building Neural Networks

This practical introduction describes the kinds of real-world problems neural network technology can solve. Surveying a range of neural;

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Models of Horizontal Eye Movements

saccades that is 3rd-order and linear, and controlled by a physiologically based time-optimal neural network. Part 3 describes a model of the;

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Neural Networks with Keras Cookbook

Implement neural network architectures by building them from scratch for multiple real-world applications. Key Features From scratch, build;

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Advanced Neural Network-Based Computational Schemes for Robust Fault Diagnosis

networks-based modelling and estimation techniques used for designing robust fault diagnosis schemes for non-linear dynamic systems. A part;

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