Methods of Pattern Inference from Symbol Sequences: Practical Computational Mechanics

Nonlinear Time Series Analysis Seminar

Max Planck Institute for the Physics of Complex Systems

February 2005


I will discuss several algorithms for pattern inference, or epsilon-machine reconstruction, from data. If the data come in the form of a symbol sequence, there are two standard inference algorithms available: the subtree merging method and causal state splitting reconstruction. If instead, the data are power spectra, other techniques are used, such as epsilon-machine spectral reconstruction or reverse Monte Carlo methods. I will contrast these methods with several examples.

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