Estimation of sensor array signal model parameters using factor analysis

Conference paper (2019)

Authors

A. Koutrouvelis Signal Processing Systems - EEMCS
R.C. Hendriks Signal Processing Systems - EEMCS
R. Heusdens Signal Processing Systems - EEMCS
Jesper Jensen Aalborg University, Oticon A/S, Denmark
Research Group
Signal Processing Systems (EEMCS) (TU Delft)
More Info
expand_more

Published Date

01-09-2019

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Microelectronics

Research Group

Signal Processing Systems

Abstract

Factor analysis is a popular tool in multivariate statistics, applied in several areas of study such as psychology, economics, chemistry and signal processing. Given a set of observed random variables, factor analysis aims at explaining and analyzing the correlation between these random variables. This is done by finding a meaningful structural model representation for the correlation matrix of the observed random variables, and subsequently estimating the underlying model parameters. In this paper, we focus on factor analysis methods applied to a commonly used signal model for sensor arrays applications and use it to jointly estimate the underlying model parameters. In addition we discuss practical considerations of these methods.

Files

08902967.pdf
(.pdf | 0.345 Mb)

Download not available