Back Propagation
Optimizing Back-Propagation using PSO_Hill and PSO_A*
... The back- propagation algorithm is used in layered feed- forward ANNs ...The back- propagation algorithm uses supervised learning, which means that we provide the algorithm with examples of ...
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Implementation of Neural Network Back Propagation Training Algorithm on FPGA
... The Back propagation training algorithm code for 4:4:2:2:4 neural network with PURELIN transfer function is implemented in ...using back propagation ...
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Implementation of Back Propagation Neural Network with PCA for Face Recognition
... implemented Back Propagation Neural Network for face recognition using MATLAB, where feature extraction and face identification system completely depend on Principal Component Analysis ...apply Back ...
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An Improved Back Propagation Neural Network Model and Its Application
... Abstrac—t-Stroke is one of the most serious disease, and the incidence rate of stroke is confirmed to be related to environmental factors including temperature, pressure and humidity .In order to obtain the relationship ...
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Back Propagation Neural Network based Emotion Recognition System
... Back propagation neural network is shown in schematic form in Fig ...it. Back propagation method is used to modify weights during process of training to yield „learning‟ ...
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Prediction Of Heart Disease Using Back Propagation MLP Algorithm
... layer. Back Propagation Algorithm necessitates the activation function to be different between the ...a Back Propagation Algorithm. MLP Back Propagation Algorithm has also gained ...
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An Approach to Handwriting Recognition using Back Propagation Neural Network
... Whenever a character is added to the list, the input pattern is generated and added using Feature Extraction. Then the Neural Network is then trained with the given input patterns using Back-Propagation ...
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Optimizing Back Propagation using PSO Hill A* and Genetic Algorithm
... and Back Propagation (BP) algorithm, referred to as HPSOBP algorithm, is proposed to evolve the optimum large neural network structure, connecting weights and bias values for one-day ahead electric load ...
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PRIVACY PRESERVING BACK PROPAGATION NEURAL NETWORK IN CLOUD COMPUTING
... we can reduce the accuracy loss by about 1% which outperforms the existing schemes. This is because introduce accuracy losses not only in the approximation of the activation function, but also during the mapping of real ...
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Rice seeds identification based on back propagation neural network model
... Abstract: Rice quality directly affects the final rice yield. In order to achieve rapid, non-destructive testing of rice seeds, this paper combines the three-dimensional laser scanning technology and back ...
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Face Detection and Recognition using Back Propagation Neural Network (BPNN)
... and fastest growing biometric areas during the last several years and become the most successful application in image processing and broadly used in security systems. A real-time system for recognizing faces using mobile ...
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A new back propagation neural network optimized with cuckoo search algorithm
... In order to overcome the weaknesses of the conventional BP, this paper proposed a new meta-heuristic search algorithm, called cuckoo search back propagation (CSBP). Cuckoo search (CS) is developed by Yang ...
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Detection of architectural distortion using multilayer back propagation neural network
... It is hypothesized that screening mammograms obtained prior to the detection of breast cancer could contain subtle signs of early stages of breast cancer such as architectural distortion in specific. The methods are ...
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Medical Image Security Using Watermarking In Back Propagation Neural Network
... [3] Poorvi Saxena and Murlidhar Vishwakarma, “A Digital WatermarkingAlgorithm Based onWavelet Packet Transform and RBF Neural Network”, 2013. [4] Hung-Hsu Tsaia, Yu-Jie Jhuanga and Yen-Shou Lai, “An SVD-Based Image ...
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Power Quality Improvement by Back Propagation Control Algorithm Using DSTATCOM
... The back propagation algorithm looks for the minimum of the error function in weight space using the method of gradient descent. This method is not only more general than the usual analytical derivations, ...
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Learning Dynamic Generator Model by Alternating Back-Propagation through Time
... The main contribution of this paper lies in the combination of the dynamic generator model and the alternating back- propagation through time algorithm. Both the model and al- gorithm are simple and ...
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Brain Tumor Detection and Classification with Feed Forward Back Propagation Network
... Imaging (MRI) is a medical imaging technique used to visualize the internal structure of the body and provide high quality images. MRI contains useful and fine information which is used to improve diagnosis accuracy. ...
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Resilient Back Propagation Algorithm in the Prediction of Mother to Child Transmission of HIV
... resilient back-propagation neural network is eva- luated in this study by two different criteria which were used to select the best model on the testing ...
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THE USE OF BACK-PROPAGATION ALGORITHM IN THE ESTIMATION OF FIRM PERFORMANCE
... Recently, many researches have been made to find the impact of human resources on firm performance. Many of these studies are conducted on the basis of statistical approaches and find the correlation between the human ...
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Optimizing Back-Propagation Gradient for Classification by an Artificial Neural Network
... the back-propagation of the gradient, which operates an iterative approximation along the line of the steepest slope, could be improved by the conjugate gradient algorithm with the search for a minimum ...
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