Abstract
In this article we propose a simple method to estimate the complexity of a finite word written over a finite alphabet. We use the notion of subword complexity (which is equal to the number of different subwords in the word) as a starting point and show the computation difficulties connected with the usage of subword complexity. To avoid them we propose a new simple measure of a word's complexity, which turned out to be not only easy to compute, but also more precise than classical subword complexity.
Received: 2010-10-11
Accepted: 2011-02-07
Published Online: 2011-05-02
Published in Print: 2011-June
© de Gruyter 2011
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Artikel in diesem Heft
- To Anatolii Volodymyrovych Skorokhod's memory
- Preface
- Almost sure asymptotic stability and convergence of stochastic Theta methods applied to systems of linear SDEs in
- Strong uniform consistency of a nonparametric estimator of a conditional quantile for censored dependent data and functional regressors
- Central limit theorem associated with bilinear random fields
- Almost sure exponential stability of the Euler–Maruyama approximations for stochastic functional differential equations
- An improvement of subword complexity
- Estimation of the long memory parameter in stochastic volatility models by quadratic variations
Schlagwörter für diesen Artikel
Subword complexity;
Kolmogorov complexity;
compressibility
Artikel in diesem Heft
- To Anatolii Volodymyrovych Skorokhod's memory
- Preface
- Almost sure asymptotic stability and convergence of stochastic Theta methods applied to systems of linear SDEs in
- Strong uniform consistency of a nonparametric estimator of a conditional quantile for censored dependent data and functional regressors
- Central limit theorem associated with bilinear random fields
- Almost sure exponential stability of the Euler–Maruyama approximations for stochastic functional differential equations
- An improvement of subword complexity
- Estimation of the long memory parameter in stochastic volatility models by quadratic variations