A modified recurrent cascade-correlation network for radar signal pulse detection

Author

Karunanithi, N. ; Whitley, D. ; Newman, D.

Author_Institution

Bellcore, Morristown, NJ, USA

fYear

1993

fDate

6-9 Sep 1993

Firstpage

497

Lastpage

506

Abstract

A Jordan-style cascade-correlation architecture is developed for radar signal pulse detection. The cascade-correlation learning architecture is modified to facilitate hardware implementation of the network. The network is constructed using only two hidden layers, with nodes added to the layers in a lateral fashion. Comparisons to networks trained using backpropagation and genetic algorithms indicates that the cascade-correlation architecture trains approximately 50 times faster and produces much better generalization

Keywords

backpropagation; correlation methods; genetic algorithms; learning (artificial intelligence); radar signal processing; recurrent neural nets; signal detection; Jordan-style cascade-correlation architecture; backpropagation; genetic algorithms; learning architecture; neural nets; radar signal pulse detection; recurrent cascade-correlation network; Backpropagation algorithms; Computer science; Detectors; Event detection; Frequency; Genetics; Instruments; Radar detection; Signal detection; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks for Processing [1993] III. Proceedings of the 1993 IEEE-SP Workshop

Conference_Location

Linthicum Heights, MD

Print_ISBN

0-7803-0928-6

Type

conf

DOI

10.1109/NNSP.1993.471838

Filename

471838