DocumentCode :
3402547
Title :
Homomorphic detection of convolved signals using class 1 filters
Author :
Lindquist, Cluade S. ; Cox, Steven W.
Author_Institution :
Dept. of Electr. & Comput. Eng., Miami Univ., FL, USA
fYear :
1991
fDate :
14-17 May 1991
Firstpage :
486
Abstract :
It is shown that signals which are convolutionally combined can be detected using optimal homomorphic filtering. The system uses Fourier transforms combined with a log[ ] operator. Dual-channel filtering is described. Single-channel filtering is also possible but does not perform as well. A simulation is presented to demonstrate the computations involved. Although Class 1 algorithms were used for simplicity, the techniques have been extended using Class 2 algorithms. Excellent results are also obtained. This homomorphic filtering technique can be used to solve a variety of problems that cannot otherwise be solved using classical methods
Keywords :
digital filters; filtering and prediction theory; signal detection; signal processing; Fourier transforms; class 1 filters; convolved signal detection; dual channel filtering; homomorphic filtering technique; optimal homomorphic filtering; Additive noise; Biology computing; Convolution; Fourier transforms; Frequency domain analysis; Nonlinear filters; Phase detection; Signal detection; Speech processing; Wiener filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1991., Proceedings of the 34th Midwest Symposium on
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-0620-1
Type :
conf
DOI :
10.1109/MWSCAS.1991.252201
Filename :
252201
Link To Document :
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