Memory order decomposition of symbolic sequences
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Volume
104
Pagination
014112 - 014112
Publisher
DOI
10.1103/physreve.104.014112
Journal
Physical Review E
Issue
ISSN
2470-0045
Metadata
Show full item recordAbstract
We introduce a general method for the study of memory in symbolic sequences based on higher-order Markov analysis. The Markov process that best represents a sequence is expressed as a mixture of matrices of minimal orders, enabling the definition of the so-called memory profile, which unambiguously reflects the true order of correlations. The method is validated by recovering the memory profiles of tunable synthetic sequences. Finally, we scan real data and showcase with practical examples how our protocol can be used to extract relevant stochastic properties of symbolic sequences.
Authors
Alvarez-Rodriguez, U; Latora, VCollections
- Mathematics [1436]