Identification of sparse FIR systems using a general quantisation scheme

Boris I. Godoy, Juan C. Agüero, Rodrigo Carvajal, Graham C. Goodwin, Juan I. Yuz

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


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.

Original languageEnglish
Pages (from-to)874-886
Number of pages13
JournalInternational Journal of Control
Issue number4
StatePublished - 3 Apr 2014
Externally publishedYes


  • Maximum likelihood
  • Quantised systems
  • Sparsity
  • System identification


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