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Addendum to ‘A stochastic algorithm to compute optimal probabilities in the chaos game’: a new convergence criterion

Part of: Communication, information Markov processes

Published online by Cambridge University Press:  01 July 2016

Laura M. Morato  and
Paola Siri
Laura M. Morato*
Affiliation:
Università di Verona
Paola Siri*
Affiliation:
Università di Verona
*
∗ Postal address: Dipartimento di Informatica, Settore di Matematica, Facoltà di Scienze MM.FF.NN., Ca' Vignal 2, Strada le Grazie 15, 37134 Verona, Italy.
∗ Postal address: Dipartimento di Informatica, Settore di Matematica, Facoltà di Scienze MM.FF.NN., Ca' Vignal 2, Strada le Grazie 15, 37134 Verona, Italy.
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Abstract

We propose a new convergence criterion for the stochastic algorithm for the optimization of probabilities (SAOP) described in an earlier paper. The criterion is based on the dissection principle for irreducible finite Markov chains.

Keywords

Image datastochastic algorithmMarkov chainmartingale

MSC classification

Primary: 94A08: Image processing (compression, reconstruction, etc.)
Secondary: 60J20: Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.)
Type
General Applied Probability
Information
Advances in Applied Probability , Volume 36 , Issue 1 , March 2004 , pp. 318 - 323
Copyright
Copyright © Applied Probability Trust 2004 

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References

[1] Morato, L. M. and Siri, P. (2001). A stochastic algorithm to compute optimal probabilities in the chaos game. Adv. Appl. Prob. 33, 423–436.CrossRefGoogle Scholar