DocumentCode
295986
Title
The modified probabilistic neural network as a nonlinear correlator detector
Author
Zaknich, Anthony ; Attikiouzel, Yianni
Author_Institution
Dept. of Electr. & Electron. Eng., Western Australia Univ., Nedlands, WA, Australia
Volume
1
fYear
1995
fDate
Nov/Dec 1995
Firstpage
309
Abstract
A nonlinear correlator detector for the detection of a signal class with some intra class variance is developed using the modified probabilistic neural network and the general regression neural network. An application, involving the detection of regular tone bursts transmitted over a poor and noisy radio channel subjected to fading, random noise and impulse noise effects, is used to show the effectiveness of the method as compared to a linear correlator
Keywords
correlators; fading; neural nets; probability; random noise; signal detection; statistical analysis; fading; general regression neural network; impulse noise effects; intra class variance; modified probabilistic neural network; noisy radio channel; nonlinear correlator detector; random noise; regular tone bursts; Acoustic noise; Correlators; Detectors; Fading; Gaussian noise; Matched filters; Neural networks; Nonlinear filters; Signal detection; Signal processing; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.488115
Filename
488115
Link To Document