A Deconvolution Method for Impulsive Signals using Neural-Networks

A Deconvolution Method for Impulsive Signals using Neural-Networks

This work describes a proposal method for impulsive signal deconvolution. The method uses a simple one-layer neural-network configured for implementing an adaptive filter that models the unknown inverse impulse response of the propagation media. The Levenberg-Marquardt (LM) algorithm is used for fin...

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Bibliographic Details
Published in:2006 IEEE International Symposium on Industrial Electronics Vol. 1; pp. 571 - 574
Main Authors: Molino-Minero-Re, E., Lopez-Garcia, M., Manuel-Lazaro, A., del-Rio-Fernandez, J.
Format: Conference Proceeding
Language:English
Published: IEEE 01-07-2006
Subjects:
Adaptive filters
Data acquisition
Deconvolution
Distortion measurement
Information analysis
Inverse problems
Materials testing
Signal analysis
Signal processing
Structural beams
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Summary:This work describes a proposal method for impulsive signal deconvolution. The method uses a simple one-layer neural-network configured for implementing an adaptive filter that models the unknown inverse impulse response of the propagation media. The Levenberg-Marquardt (LM) algorithm is used for finding the coefficients of the neural-network. The method has been tested on simulated channels, and on a mathematical model from a real cantilever beam. Results show that with proper training deconvolution can be achieved
ISBN:9781424404964
1424404967
ISSN:2163-5137
DOI:10.1109/ISIE.2006.295521