Classification of bandlimited FSK4 and FSK8 signals

Vis Ramakonar, Daiyoush Habibi, Abdesselam Bouzerdoum

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

This paper compares two types of classifiers applied to bandlimited FSK4 and FSK8 signals. The first classifier employs the decision-theoretic approach and the second classifier is a neural network structure. Key features are extracted using a zero crossing sampler. A novel decision tree is proposed and optimum threshold values are found for the decision theoretic approach. For the neural network, the optimum structure is found to be the smallest structure to give 100% overall success rate. The performance of the both classifiers has been evaluated by simulating bandlimited FSK4 and FSK8 signals corrupted by Gaussian noise. It is shown that the neural network outperforms the decision-theoretic approach particularly for SNR <10 dB.

Original languageEnglish
Title of host publication6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis
PublisherIEEE Computer Society
Pages398-401
Number of pages4
ISBN (Print)0780367030, 9780780367036
DOIs
Publication statusPublished - 2001
Externally publishedYes
Event6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Kuala Lumpur, Malaysia
Duration: 13 Aug 200116 Aug 2001

Publication series

Name6th International Symposium on Signal Processing and Its Applications, ISSPA 2001 - Proceedings; 6 Tutorials in Communications, Image Processing and Signal Analysis
Volume2

Conference

Conference6th International Symposium on Signal Processing and Its Applications, ISSPA 2001
Country/TerritoryMalaysia
CityKuala Lumpur
Period13/08/0116/08/01

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