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7 articles for “BPN network”
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Optical Character Recognition Using Back Propagation Neural Network
Abstract: This paper represents an Artificial Neural Network (ANN)-based approach for the recognition of English characters using feed-forward neural network. Noise has been considered as one of the major issues that degrades the performance of character recognition system. Our feed forward network has one input, one hidden, and one output layer. The entire recognition system is divided into two sections, namely training and recognition section. Both the sections include image acquisition, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 11–18 Read article
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Signature Based Human Behaviour Prediction
Abstract: Earlier personality or behavior of a person was predicted by spending lot of time with the person. As we know, spending time with person is very difficult task. Concerning this problem, in the present study a method has been proposed for the behavioral prediction of a person through signature analysis. The prediction is done from four features which are alignment, thickness, shape and pen pressure as found in individual’s signature. …
Published in Recent Trends in Programming languages · Vol. 2, Issue 2, 2015 · pp. 13–21 Read article
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Performance Comparison between Back-Propagation Learning and Kohonen Self-Organizing Neural Networks Algorithm in Terms of Pattern Recognition
Abstract: Pattern recognition using back-propagation learning and Kohonen self-organizing neural network algorithms has been developed and measured various performance based on different criteria and environment of the pattern. These pattern recognition systems have taken the object image as input. In image pre-processing stage, scaling and clipping process has been applied from the background image to avoid unnecessary portion of the object image. Feature extraction has been performed after applying filtering and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 1–8 Read article
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Power Estimation for VLSI Circuits Using Neural Networks
Abstract: Neural network based VLSI power estimation is done which estimates power in VLSI circuits from its input/output and gate information, without simulation and analysis of its detail structure and the interconnections.Artificial neural network is created which helps in estimation of power. Power estimation results from the [2] [3]are used as the training vector for the network .The network is trained using Back-propagation algorithm. Asimple recurrent network is also introduced called …
Published in Journal of VLSI Design Tools and Technology · Vol. 1, Issue 1-2-3, 2011 · pp. 45–56 Read article
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Speed Estimator for Sensorless Field-Oriented Control Induction Motor Drive Using Intelligent Neural Networks
Abstract: This paper presents a novel approach to the field-oriented control (FOC) of induction motor drives. It discusses the introduction of artificial neural networks (ANNs) for decoupling control of induction motors using FOC principles. The neural network has been then designed and trained online by employing a back propagation network (BPN) algorithm. The estimator was designed and simulated in Matlab/Simulink. Simulation result shows a good performance of speed estimator. Simulation results …
Published in Journal of Control & Instrumentation · Vol. 6, Issue 3, 2015 · pp. 42–49 Read article
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Bearing Defect Diagnosis: An Approach for Manufacturing Industries Using Wavelet Transform Based Features
Abstract: To maintain reliability in the manufacturing units, industries have concentrated their attention on the condition based maintenance. Fault detection and diagnosis are the two of three condition based maintenance mainstays. Bearing is one of the most important and essential components of the rotating machines. Hence, the researchers have shown their interest in bearing fault detection and diagnosis from the last few years. They mainly use bearing vibration as fault characteristics …
Published in Journal of Microelectronics and Solid State Devices · Vol. 4, Issue 1, 2017 · pp. 15–21 Read article
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article