Title :
Neural network model based on weights and unit-offset control
Author :
Lim, Chunhwan ; Park, Jongan
Author_Institution :
Dept. of Electron. Eng., Chosun Univ., Kwangju, South Korea
Abstract :
In this paper, we propose an improved algorithm for a neural network. It consists of multilayer neural networks with control part and address memory part. The control part controls weights between the input layer and the hidden layer, controls unit offsets of the hidden layer, and sends the output data to the address memory part. The address memory part memorizes the output pattern of the hidden layer, compared with the input pattern and sends the learning data to the output layer after learning. Simulation results show that it is easy to control weights and unit-offset. Its convergence speed is fast
Keywords :
backpropagation; multilayer perceptrons; address memory part; convergence speed; hidden layer; improved algorithm; input layer; multilayer neural networks; neural network model; unit-offset control; weights; Backpropagation algorithms; Convergence; Electronic mail; Equations; Error correction; Learning systems; Multi-layer neural network; Neural networks; Neurons; Weight control;
Conference_Titel :
Signal Processing, 1996., 3rd International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-2912-0
DOI :
10.1109/ICSIGP.1996.566572
