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

fYear

2006

fDate

6-10 Nov. 2006

Firstpage

3304

Lastpage

3307

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;

fLanguage

English

Publisher

ieee

Conference_Titel

IEEE Industrial Electronics, IECON 2006 - 32nd Annual Conference on

Conference_Location

Paris

ISSN

1553-572X

Print_ISBN

1-4244-0390-1

Type

conf

DOI

10.1109/IECON.2006.347513

Filename

4153114

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2366154