Statistical properties of the taxonomic classification of human languages are studied. It is shown that, at the highest levels of the taxonomic hierarchy, the frequency of taxon members as a function of the number of languages belonging to each member decays as a power law. This feature reveals that a self-similar structure underlies the taxonomy of languages, exactly as observed in the taxonom...

Given a set of data, recorded by observing the decisions of an expert player, we present a case-based framework that allows the successful generalisation of those decisions in the game of no limit Texas Hold’em. We address the problems of determining a suitable action abstraction and the resulting state translation that is required to map real-value bet amounts into a discrete set of abstract a...

In this note we provide two alternative proofs to that given in [15] of the fact that the best possible lower bound for the set of n-quasi-copulas does not induce a stochastic measure on [0, 1]n for n ≥ 3: firstly, by reviewing its mass distribution, and secondly, by using concepts of self-affinity.

We consider the late time behaviour of non–tilted perfect fluid Bianchi VII0 models when the source is a radiation fluid, thereby completing the analysis of the Bianchi VII0 models initiated by Wainwright et al in a recent paper. The models exhibit the phenomena of asymptotic self-similarity breaking and Weyl-curvature dominance at late times. The late time dynamics of the VII0 perfect fluid mo...

Within the framework of generalized combinatorial approach, the complexity is determined for infinite set of self-similar hierarchical ensembles. This complexity is shown to increase with strengthening of the hierarchy coupling to the value, which decreases with growth of both scattering of this coupling and non-extensivity parameter.

We shall show that the oscillations observed by Strichartz JRS92, Str90] in the Fourier transforms of self-similar measures have a large-scale renormali-sation given by a Riesz-measure. Vice versa the Riesz measure itself will be shown to be self-similar around every triadic point.

In this paper, we present a novel framework for analyzing video using self-similarity. Video scenes are located by analyzing inter-frame similarity matrices. The approach is flexible to the choice of similarity measure and is robust and data-independent because the data is used to model itself. We present the approach and its application to scene boundary detection. This is shown to dramaticall...