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Open AccessArticle

Syntactic Parameters and a Coding Theory Perspective on Entropy and Complexity of Language Families

Department of Mathematics, California Institute of Technology, Pasadena, CA 91125, USA
Academic Editors: Frédéric Barbaresco, Frank Nielsen and Kevin H. Knuth
Entropy 2016, 18(4), 110; https://doi.org/10.3390/e18040110
Received: 14 January 2016 / Revised: 13 March 2016 / Accepted: 18 March 2016 / Published: 7 April 2016
(This article belongs to the Special Issue Differential Geometrical Theory of Statistics)
We present a simple computational approach to assigning a measure of complexity and information/entropy to families of natural languages, based on syntactic parameters and the theory of error correcting codes. We associate to each language a binary string of syntactic parameters and to a language family a binary code, with code words the binary string associated to each language. We then evaluate the code parameters (rate and relative minimum distance) and the position of the parameters with respect to the asymptotic bound of error correcting codes and the Gilbert–Varshamov bound. These bounds are, respectively, related to the Kolmogorov complexity and the Shannon entropy of the code and this gives us a computationally simple way to obtain estimates on the complexity and information, not of individual languages but of language families. This notion of complexity is related, from the linguistic point of view to the degree of variability of syntactic parameter across languages belonging to the same (historical) family. View Full-Text
Keywords: syntax; principles and parameters; error-correcting codes; asymptotic bound; Kolmogorov complexity; Gilbert–Varshamov bound; Shannon entropy syntax; principles and parameters; error-correcting codes; asymptotic bound; Kolmogorov complexity; Gilbert–Varshamov bound; Shannon entropy
MDPI and ACS Style

Marcolli, M. Syntactic Parameters and a Coding Theory Perspective on Entropy and Complexity of Language Families. Entropy 2016, 18, 110.

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