Identification of sparse FIR systems using a general quantisation scheme

Title: Identification of sparse FIR systems using a general quantisation scheme
Creator: Godoy, Boris I.; Agüero, Juan C.; Caravajal, Rodrigo; Goodwin, Graham C.; Yuz, Juan I.
Relation: International Journal of Control Vol. 87, Issue 4, p. 874-886
Publisher Link: http://dx.doi.org/10.1080/00207179.2013.861611
Publisher: Taylor & Francis
Resource Type: journal article
Date: 2014
Description: This paper presents an identification scheme for sparse FIR systems with quantised data. We consider a general quantisation scheme, which includes the commonly deployed static quantiser as a special case. To tackle the sparsity issue, we utilise a Bayesian approach, where an ℓ₁ a priori distribution for the parameters is used as a mechanism to promote sparsity. The general framework used to solve the problem is maximum likelihood (ML). The ML problem is solved by using a generalised expectation maximisation algorithm.
Subject: system identification; quantised systems; maximum likelihood; sparsity
Identifier: http://hdl.handle.net/1959.13/1306905
Identifier: uon:21286
Identifier: ISSN:0020-7179
Language: eng
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