DocumentCode
296039
Title
Performance improvements for a neural network detector
Author
Andina, Diego ; Sanz-GonzÁlez, José L. ; Rodríguez-Martin, Octavio A.
Author_Institution
ETSI Telecomunicacion, Univ. Politecnica de Madrid, Spain
Volume
1
fYear
1995
fDate
Nov/Dec 1995
Firstpage
492
Abstract
In this paper, a neural detector is purposed. It can be applied to binary detection problems such as those found in radar or sonar. Topics about designing the structure, training procedure and evaluating the performance, are discussed. The detector optimization is based on the use of a criterion function that yields a solution significantly superior to the typical sum-of-square-error. Using a modeled input, its performance is evaluated by Monte Carlo trials. As a result, receiver operating characteristics and detection curves are presented
Keywords
Monte Carlo methods; acoustic signal detection; backpropagation; multilayer perceptrons; probability; radar detection; Monte Carlo trials; binary detection problems; detection curves; neural network detector; performance evaluation; radar; receiver operating characteristics; sonar; sum-of-square-error; training procedure; Detectors; Envelope detectors; Least squares approximation; Monte Carlo methods; Neural networks; Optical noise; Radar detection; Robustness; Sonar applications; Sonar detection; Telecommunication standards; Very large scale integration;
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.1995.488226
Filename
488226
Link To Document