backpropagation

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back·prop·a·ga·tion

 (băk′prŏp′ə-gā′shən)
n.
A common method of training a neural net in which the initial system output is compared to the desired output, and the system is adjusted until the difference between the two is minimized.
American Heritage® Dictionary of the English Language, Fifth Edition. Copyright © 2016 by Houghton Mifflin Harcourt Publishing Company. Published by Houghton Mifflin Harcourt Publishing Company. All rights reserved.
References in periodicals archive ?
Radial bias functions are used in back propagation neural nets.
The results of the AR analysis are used for the input of different ANN models which are Feed Forward Back Propagation and Cascade Forward Back Propagation Models.
In 2014 another face recognition approach, that has the ability to extract face direction information effectively, is proposed that utilizes regional directional weighted local binary pattern and the extracted characteristic vector classification was done by Chi-square [FEN 14] .In order to enhance the recognition rate robustness, the proposed method uses Gabor features in biorthogonal wavelet domain for feature extraction phase and back propagation neural network model for classification phase.
In this study, a multi layer feed forward back propagation network was created with Levenberg-Marquardt's learning algorithm and sigmoidal transfer function to predict the MFP.
In this paper the back propagation learning algorithm in the form of supervised learning is adapted to recognize license plate numbers and model types of vehicles driving in Korea.
Back propagation algorithm is an efficient learning algorithm used in ANN.
The back Propagation algorithm can be viewed as an application of optimization method known in statistics as stochastic approximation.
In this work back propagation neural network classifier is used for classification.
Feed forward back propagation network (FFBPN) and recurrent neural network (RNN) are most used networks type [14-15].
So, the C-RNN model can be trained end-to-end and the identification error is minimized by stochastic gradient descent with truncated back propagation through time (BPTT).
Mi, "Linear Discriminant Analysis and Back Propagation Neural Network Cooperative Diagnosis Method for Multiple Faults of Complex Equipment Bearings," Acta Armamentarii, vol.