Share Email Print
cover

Proceedings Paper

Probabilistic feedforward neural network
Author(s): Bharathi B. Devi
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

In this paper, we propose a Gaussian neuron model for feedforward type of neural networks and a method to adapt the above network for any input, not necessarily in the range [0,1]. An error function based on the class label and a priori probability is defined and gradient descent procedure, with backpropagating error, is used for finding the optimal set of parameters of this network. Different approaches are proposed for increasing the rate of convergence of this network. Experimental results are given for continuous data from speech waveform and XOR type of data.

Paper Details

Date Published: 10 October 1994
PDF: 12 pages
Proc. SPIE 2353, Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision, (10 October 1994); doi: 10.1117/12.188906
Show Author Affiliations
Bharathi B. Devi, DSC Communication Corp. (United States)


Published in SPIE Proceedings Vol. 2353:
Intelligent Robots and Computer Vision XIII: Algorithms and Computer Vision
David P. Casasent, Editor(s)

© SPIE. Terms of Use
Back to Top