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37 articles for “back-propagation algorithm”
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Faulty Object Detection by Image Processing Based on Modified Back-Propagation Algorithm of Artificial Neural Network
Abstract: The conventional algorithms such as canny edge detection require so much computation which makes it more time consuming. Hence it is not used for industrial applications such as damage detection because each product should be analyzed in a fraction of seconds so that the manufacturing rate of the industry should not be affected. Hence Artificial Neural Network can be used for edge detection. Though it requires a lot of time …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 2, 2016 · pp. 19–25 Read article
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Performance Analysis of Fusion Classifier of Face Recognition System based on ANN and GA
Abstract: Though a lot of significant work has been done for recognizing and improving the performance in facial pattern, most techniques have been developed based on a single classifier. But most often, the performance of the classifier is not satisfactory in some case. It has been proposed that the performance of face recognition will beimproved by fusing two or more classifiers. We can combine the information/data in different level i.e., feature …
Published in Current Trends in Information Technology · Vol. 4, Issue 1, 2014 · pp. 4–13 Read article
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Decision Fusion based Pair of Iris Recognition using Back-Propagation Learning Neural Network Algorithm
Abstract: AbstractThe contribution of this work is to enhance the performance of the iris recognition system through decision fusion of left and right iris pattern. Iris recognition system performs well and identify human correctly in neutral environment. In this paper a pair of iris recognition system has been proposed, which is capable enough to identify human through noisy environments. Principal component analysis based dimensionality reduction technique has been used toreduce and …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 1–6 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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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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Controller Performance Assessment (CPA) of Intelligent Control for Non-linear System
Abstract: The objective of this paper is to design and undertake comparative analysis of classical and intelligentcontrollers for nonlinear system. These controllers are compared based on controller performanceassessment in which the different parameters as overshoot, steady-state error, rise time, settling time,response of reference change and output variance are analyzed. To achieve these objectives, the water tankcontrol problem as nonlinear system has been built in Simulink and implementations traditionally classicalcontroller and advance …
Published in Journal of Control & Instrumentation · Vol. 1, Issue 1-2-3, 2011 · pp. 25–33 Read article
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Artificial Neural Network Model for Stock Market Forecasting
Abstract: AbstractIn recent years, many attempts have been made to predict the behavior of bonds, currencies, stocks or stock markets. Neural networks, as an intelligent data mining method, have been used in many different challenging pattern recognition problems such as stock market prediction. The aim of this paper is to predict stock market using artificial neural networks (ANNs). The authors used feed forward neural network trained by back-propagation algorithm to make …
Published in Journal of Computer Technology & Applications · Vol. 5, Issue 1, 2014 · pp. 7–12 Read article
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FIR Filter Design using Artificial Neural Network
Abstract: In this paper design a low pass FIR filter by artificial neural network. For this kind of application, a different type of model is used in ANN. In this work, MLP Back propagation algorithm is used to train the Neural Network. MLP network is very effective method for filter designing process. We also compare the result of this method and the normal mathematical method. Keywords: Neural network, MLP back propagation, …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 3, Issue 3, 2013 · pp. 29–35 Read article
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Enhancing Data Security Via the Application of Back- Propagation Feed-Forward Methods in Encryption
Abstract: The computer society uses a variety of automated methods for file security and data storage. Several organisations are concerned about the information exchange via an unsecured network for a distributed architecture, such as the time-sharing and real-time system. Probably the most crucial element that contributes to effective security is cryptography. Using a constant weighted factor for boosting the factor, the study aims at extending or updating the earlier presented Artificial …
Published in Journal of Open Source Developments · Vol. 9, Issue 3, 2022 · pp. 13–17 Read article
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Artificial Neural Network Implementation in FPGA using Multiplexer-based Weight Updating for Efficient Resource Utilization
Abstract: This paper presents a novel scheme for field-programmable gate array (FPGA) implementation of an artificial neural network (ANN). The proposed implementation is aimed at reducing resource requirement, without compromising on the speed so that a complex ANN architecture could be realized on a single chip at a lower cost. The weight updating process in different layers of the ANN has been carried using a simple MUX-based architecture. Backpropagation algorithm which …
Published in Journal of Semiconductor Devices and Circuits · Vol. 2, Issue 1, 2015 · pp. 1–5 Read article
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Power Quality Monitoring in Wind Solar Hybrid System
Abstract: With the development of new functionalities, solar and wind energy based hybrid systems are upcoming energy source with higher efficiency. Solar and wind energy being naturally available in abundance and non-polluting, is one of the most promising sources. Due to the development of modern power electronic devices, the power quality of wind solar hybrid system gets affected. Hence, due to the increasing usage of sensitive electronic equipments in wind solar …
Published in Journal of Power Electronics and Power Systems · Vol. 8, Issue 1, 2018 · pp. 16–23 Read article
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Predicting Software Reliability using Artificial Neural Networks: A Review
Abstract: AbstractSoftware reliability has become a major concern for all the software systems. Predicting software reliability has become a major challenge for both the software developers and the engineers. Before the software is dispensed to the market/customers, it is thoroughly checked for any errors and if errors are there, they are thereby removed. For the purpose of reliability estimation certain mathematical software reliability models have been proposed for estimating the reliability …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 2, 2019 · pp. 14–19 Read article
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Modeling the Solar Radiation Parameter over Abuja using Neural Networks
Abstract: Many computer simulation models which predict growth, development and yield of agronomic and horticultural crops require daily weather data as input. One of these inputs is daily total solar radiation, which in many cases is not available owing to the high cost and complexity of the instrumentation needed to collect the data. In this work, a neural network model of the solar radiation over Abuja, Nigeria is developed. The model …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 6, Issue 3, 2017 · pp. 40–48 Read article
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Retina Recognition System Using Wavelet based Neural Network Algorithm
Abstract: This paper presents an approach of wavelet feature-based retina recognition system using back-propagation learning neural network algorithm. After acquiring the retinal image, at first vessels were segmented from the image. Then the feature extraction was carried out by analyzing the segmented retinal image using multiresolution analysis through the wavelet-based approach. Then extracted features were fed to the back-propagation learning neural network algorithm to create the learned template which was used …
Published in Current Trends in Signal Processing · Vol. 5, Issue 2, 2015 · pp. 35–39 Read article
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Multi-Layer Perceptron Neural Network Based Person Identification Using Appearance Based Facial Feature
Abstract: This paper deals with secure person identification system using Back-Propagation learning neural network algorithm where appearance based facial feature and Principal Component Analysis based dimensionality reduction technique have been used. To extract the appearance based facial features, Viola-Jones method has used as a face detector, Stam’s method of Active Shape Model has applied for detecting the facial edges and image pre-processing method has used for eliminating the background noises. For …
Published in Current Trends in Signal Processing · Vol. 4, Issue 1, 2014 · pp. 26–34 Read article
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Optimizing Routing and Placement of VLSI Circuits with Differential Algorithms and Neural Networks
Abstract: The performance of modern VLSI systems is heavily influenced by power constraints, necessitating precise power estimation and effective optimization techniques. Traditional methods, such as gate-level simulations, are often slow and computationally intensive. This paper introduces DRPENN (Differential Algorithm for Routing and Placement Optimization using Neural Networks), an innovative solution that combines a Switching Activity Estimator (SAE) with a neural network-assisted differential algorithm. By leveraging toggle rates from simulations to train …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 2, 2024 · pp. 14–20 Read article
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Simulation of Neural Network based PID Controller for Pressure Process
Abstract: This paper provides a Neural Network PID controller based on Back Propagation (BP) algorithm applied to pressure control in a tank. The controller has many advantages like that more convenient in parameter regulating, better robust. Neural network is to adjust the parameters of PID controller based on the operational status of the system, to achieve a better performance, making the output of the output neurons corresponding to the three adjustable …
Published in Journal of Control & Instrumentation · Vol. 4, Issue 1, 2013 · pp. 23–27 Read article
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Prediction of shear strength of reinforced concrete beams using Artificial Neural Network and evaluated by Finite Element Software
Abstract: ABSTRACTIn this paper, the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference Framework (ANFIS) are utilized to foresee the shear quality of Reinforced Concrete (RC) shafts, and the models are contrasted and American Concrete Institute (ACI) and Iranian Concrete Institute (ICI) observational codes. The ANN display, with Multi-Layer Perceptron (MLP), utilizing a Back-Propagation (BP) algorithm, is utilizedto foresee the shear quality of RC pillars. Six vital parameters are chosen …
Published in Journal of Construction Engineering, Technology & Management · Vol. 8, Issue 1, 2018 · pp. 34–42 Read article
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Comparison of RSM and ANN Modeling Approaches in Predicting the Laser Phase Transformation Hardening Parameters on the Heat Input and Hardened-Bead Profile Quality of Unalloyed Titanium
Abstract: In the present work, laser transformation hardening (LTH) of unalloyed titanium, nearer to ASTM Grade 3 of chemical composition was investigated using CW 2kW, Nd: YAG laser. The laser process variables such as laser power, scanning speed, and focused position play a major role in deciding the laser hardened bead quality. Two methods, Response Surface Methodology (RSM) and Artificial Neural Network (ANN) were used to predict the heat input and …
Published in Journal of Materials & Metallurgical Engineering · Vol. 5, Issue 1, 2015 · pp. 36–59 Read article
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Design of Beam using Artificial Neural Network based Approach
Abstract: Recent developments in artificial neural network (ANN) have opened up new possibilities in the field of structural engineering. This paper demonstrates the applicability of ANN for the design of beams subjected to moment and shear. An attempt has been made to capture the mapping between the design variables using ANN. There is no direct method for design of beams. A feed forward network and back propagation training algorithm has been …
Published in Recent Trends in Civil Engineering & Technology · Vol. 4, Issue 3, 2014 · pp. 1–6 Read article