In this paper a new neural network model with weight-function is proposed. In the model, the weight is a function with adjustable parameters, and the sum of these weight functions as the neuron output. And according to BP algorithm, the learning algorithm of feed-forward neural network with weight-function neurons is studied. Simulation results show that, applying the back-propagation algorithm to the new neural network the better convergence rate can be obtained and in some applications the new neural network based on the weight-function neurons is superior to the BP network based on the MP neuron model, so that it has a significant value in further research and application.

Date Published: 13 March 2013
PDF: 6 pages
Proc. SPIE 8784, Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies, 87840L (13 March 2013); doi: 10.1117/12.2013811

Published in SPIE Proceedings Vol. 8784:
Fifth International Conference on Machine Vision (ICMV 2012): Algorithms, Pattern Recognition, and Basic Technologies
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)