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Pattern Recognition Letters
Volume 24, Issue 15, November 2003, Pages 2823-2827
 
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doi:10.1016/S0167-8655(03)00136-3    
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Copyright © 2003 Elsevier B.V. All rights reserved.

Signal recognition: Fourier transform vs. Cosine transform

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L. GelmanCorresponding Author Contact Information, E-mail The Corresponding Author, M. Sanderson and C. Thompson

Department of Process and Systems Engineering, Cranfield University, Cranfield MK 43 OAL, UK


Received 19 September 2002; 
revised 18 March 2003. 
Available online 25 June 2003.

Abstract

A new feature representation approach, the simultaneous usage of the real and imaginary Fourier components with taking into account the covariance between these components, was compared with the Cosine transform approach for Gaussian recognition.

Author Keywords: Statistical recognition; Real and imaginary Fourier components; Cosine transform; Likelihood ratio

Article Outline

1. Introduction
2. Theoretical analysis
3. Conclusion
Appendix A
References

Corresponding Author Contact InformationCorresponding author. Tel.: +44-1234-750111x5425


Pattern Recognition Letters
Volume 24, Issue 15, November 2003, Pages 2823-2827
 
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