Title :
Inverse Filtering Approximation for Impacting Signals Estimation Using a Multilayer Neural Network
Author :
Molino-Minero-Re, E. ; Garcia, Mariano Lopez ; Lazaro, Antoni Manuel ; Fernandez, Joaquin Del Rio
Author_Institution :
SARTI, Polytech. Univ. of Catalonia, Barcelona
Abstract :
This paper describes an original method for estimating impacting signals through an inverse filter based on a multilayer neural network (NN). A model for the impacting analytical signal has been used for training the NN using the Levenberg-Marquardt (LM) learning algorithm. The method has been tested with data acquired with a single-input accelerometer. Experimental results show that with the correct number of neurons and the proper training the NN can be used as an inverse filter
Keywords :
accelerometers; filtering theory; neural nets; signal processing; Levenberg-Marquardt learning algorithm; impacting signals estimation; inverse filtering approximation; multilayer neural network; single-input accelerometer; Accelerometers; Algorithm design and analysis; Estimation; Filtering; Filters; Multi-layer neural network; Neural networks; Neurons; Signal analysis; Testing;
Conference_Titel :
IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on
Conference_Location :
Paris
Print_ISBN :
1-4244-0390-1
DOI :
10.1109/IECON.2006.347513
