Tensor-based theory for quantized piecewise-affine Markov systems: Analysis of some map families

Gianluca Setti, Riccardo Rovatti, Gianluca Mazzini

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


In this paper we consider a tensor-based approach to the analytical computation of higher-order expectations of quantized trajectories generated by Piecewise Affine Markov (PWAM) maps. We formally derive closed-form expressions for expectations of trajectories generated by three families of maps, referred to as (n, t)-tailed shifts, (n, t)-broken identities and (n, t, π)-mixing permutations. These families produce expectations with asymptotic exponential decay whose detailed profile is controlled by map design. In the (n, t)-tailed shift case expectations are alternating in sign, in the (n, t)-broken identity case they are constant in sign, and the (n, t, π)-mixing permutation case they follow a dumped periodic trend.
Original languageEnglish (US)
Pages (from-to)2090-2100
Number of pages11
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Issue number9
StatePublished - Jan 1 2001
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-02-15

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics
  • Electrical and Electronic Engineering


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