Document Type

Conference Proceeding

Publisher

IEEE and ISSPA

Faculty

Computing, Health and Science

School

Engineering and Mathematics

RAS ID

1978

Comments

This conference paper was originally published as: Ramakonar, V. S., Habibi, D. , & Bouzerdoum, A. (2001). Classification of bandlimited fsk4 and fsk8 signals. Proceedings of 6th Internatrional Symposium on Signal Processing and its Applications. (pp. 398 - 401 vol.2 ). Malaysia. IEEE and ISSPA. Original article available here

© 2001 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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

DOI

10.1109/ISSPA.2001.950164

Access Rights

free_to_read

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Link to publisher version (DOI)

10.1109/ISSPA.2001.950164