Murdoch University Research Repository

Welcome to the Murdoch University Research Repository

The Murdoch University Research Repository is an open access digital collection of research
created by Murdoch University staff, researchers and postgraduate students.

Learn more

A modified probabilistic neural network signal processor for nonlinear signals

Zaknich, A. and Attikiouzel, Y. (1997) A modified probabilistic neural network signal processor for nonlinear signals. In: 13th International Conference on Digital Signal Processing Proceedings, DSP 97, 291 - 294, Santorini, Greece pp. 291-294.

PDF - Published Version
Download (467kB)
Link to Published Version:
*Subscription may be required


This paper introduces a practical and very effective network for nonlinear signal processing called the modified probabilistic neural network. It is a regression technique which uses a single radial basis function kernel whose bandwidth is related to the noise statistics. It has special advantages in application to time and spatial series signal processing problems because it is constructed directly and simply for the training signal waveform features. A sonar signal processing problem is used to illustrate its operation and to compare it with some other filters and neural networks

Item Type: Conference Paper
Publisher: IEEE
Copyright: © 1997 IEEE
Item Control Page Item Control Page


Downloads per month over past year