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54 articles for “back propagation network”
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Iris Recognition System Using Principal Component Analysis based Back-Propagation Learning Neural Networks
Abstract: This paper deals with the iris recognition system using Back-Propagation learning neural network algorithm where Principal Component Analysis technique has been used to reduce the dimension of the iris feature vector. Automated iris localization and segmentation methods have applied to effectively isolate the iris region from pupil and sclera. Circular Hogue transform has used to detect the iris/sclera boundary and pupil/iris boundary. To remove the upper and lower eyelids effects …
Published in Current Trends in Information Technology · Vol. 3, Issue 3, 2013 · pp. 5–11 Read article
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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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Audio-Only Speaker Identification using Principal Component Analysis based Back-Propagation Learning Neural Network in Noisy Environment
Abstract: This paper introduces text dependent speaker identification system on Principal Component Analysis based Back-Propagation learning neural network which deals with detecting a particular speaker from a known populations under noisy environment. For audio pre-processing, ends point detection, silence parts removal, frame segmentation and windowing techniques have been used and wiener filter has been applied to remove the background noise from the audio speech utterances. To reduce the dimension of the …
Published in Current Trends in Signal Processing · Vol. 3, Issue 3, 2013 · pp. 1–10 Read article
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Face Detection and Recognition System Using Back- Propagation Neural Network Classifier
Abstract: Abstract Today Security is an important part of our everyday lives. Biometric technologies are used for providing and increasing the security of the organizations. Human face recognition is a potential method of biometric authentication. This paper represents a process of face detection and recognition system using principal component analysis with back-propagation neural network. For recognizing the faces there are several steps required. Principal component analysis is used for feature extraction …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 1, Issue 2, 2014 · pp. 19–24 Read article
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Analysis Of Gradient Descent In Back Propagation Neural Network For Maximum And Efficient Utilization
Abstract: The back-propagation is a successfully established algorithm for multi-layered perceptron neural networks, which is usuallywith successfully for tiny network architectures or small tasks. In this paper we have highlighted the important libraries for thepurpose of implementation of neural networks. After that we have given the process of feed forward in neural network and howwe optimize this process by updating the weights by going backward towards the previous layers. The Author …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 1, 2022 · pp. 21–30 Read article
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Back-Propagation Neural Network Based Speaker Identification Under Noise Distortion
Abstract: The aim of this paper is to evaluate the performance of the proposed speaker identification system where Wiener filtering technique has been used to eliminate the background white Gaussian noises and linear discriminant analysis has been used to reduce the dimension of the speech features. Since the audio signal captures more environmental noises than other biometrics modalities, the main emphasis of this paper is to analyze the problem domains of …
Published in Trends in Electrical Engineering · Vol. 5, Issue 2, 2015 · pp. 1–6 Read article
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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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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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Review on Evaluation Techniques Such as DOE and ANN Used for Evaluate Heat Flow Parameters for Resistance Spot Welding
Abstract: Resistance spot welding is a widely used process of metal joining in industries. In resistance spot welding process, the time of welding is very little so, during welding process maintenance of high accuracy and precision is very difficult. Resistance spot welding has a wide application in automobile industry, household and domestic appliances manufacturing industry and fabrication industry like air craft manufacturing industry. For better output quality of product, save time …
Published in Trends in Mechanical Engineering & Technology · Vol. 5, Issue 3, 2015 · pp. 26–32 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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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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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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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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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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Face Recognition Using Neural Networking Algorithms
Abstract: Face recognition system has become quite popular nowadays. It has gained a good attention in recent few years. Face recognition is practically everywhere, in security system for criminal activities, places like airports and international borders, it is needed for identification of people. In the paper, we discussed about three Neural Networking Algorithms used for FR such as Gabor Filter, Principle Component Analysis with Back Propagation Neural Network and Wavelet Transform …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 1, 2020 · pp. 23–27 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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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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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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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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Evaporation estimation using multilayer neural network – A case study for Chhattisgarh plains
Abstract: Evaporation being one of the most important components of the hydrological cycle, it is important to know its relationship with other climatic factors for developing strategies for effective water resource management especially for agricultural purposes. There are few direct and indirect methods in practice for the measurement or computation of evaporation losses. This study is conducted to demonstrate the ability of multilayer neural network (MLNN) with back propagation weight update …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 2, 2018 · pp. 89–97 Read article