A Deconvolution Method for Impulsive Signals using Neural-Networks

Autor:	Erik Molino-Minero-Re, Joaquin del-Rio-Fernandez, Mariano Lopez-Garcia, A. Manuel-Lazaro
Rok vydání:	2006
Předmět:	Blind deconvolution Adaptive filter Signal processing Artificial neural network Control theory Computer Science::Neural and Evolutionary Computation Wiener deconvolution Deconvolution Inverse problem Impulse response Mathematics
Zdroj:	2006 IEEE International Symposium on Industrial Electronics.
DOI:	10.1109/isie.2006.295521
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::915d1078d76aeca6f0afa87dfa61ba83 https://doi.org/10.1109/isie.2006.295521 Zobrazit plný text záznamu