Search Results - parallel using ann algorithm*
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Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi
Published 2015“…The ANN2 is used to update the weights and biases online while ANN1 is used to implement the controller. …”
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Application of Artificial Neural Networks (ANN) for unit commitment prediction / Robert Engkiau
Published 2003“…Results from existing Genetic Algorithm (GA) program were used as the NN training and testing data set. …”
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Parallel backpropagation neural network training for face recognition
Published 2023“…In this paper, we describe implementation of ANN training process using backpropagation learning algorithm for exploiting the high performance SIMD architecture of GPU using CUDA. …”
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Electromygraphy (EMG) signal based hand gesture recognition using Artificial Neural Network (ANN)
Published 2011“…The purpose of this paper is to describe the process of detecting different predefined hand gestures (left, right, up and down) using artificial neural network (ANN). ANNs are particularly useful for complex pattern recognition and classification tasks. …”
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EMG motion pattern classification through design and optimization of neural network
Published 2012“…The ANN models work in parallel thus providing higher computational performance than traditional classifiers which function sequentially. …”
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A modified artificial neural network (ANN) algorithm to control shunt active power filter (SAPF) for current harmonics reduction
Published 2013“…This paper depicts artificial intelligence (AI) application on resolving the power quality problem mentioned above by using the parallel active power filter (APF) strategy in two-wire distribution systems. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Published 2011“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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EMG motion pattern classification through design and optimization of Neural Network
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