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Tight bounds on the block entropy of patterns of sequences generated by independent and identically distributed (i.i.d.) sources are derived. A pattern of a sequence is a sequence of integer indices with each index representing the order of…

Information Theory · Computer Science 2007-11-14 Gil I. Shamir

Bounds on the entropy of patterns of sequences generated by independently identically distributed (i.i.d.) sources are derived. A pattern is a sequence of indices that contains all consecutive integer indices in increasing order of first…

Information Theory · Computer Science 2007-07-13 Gil I. Shamir

Finding the underlying probability distributions of a set of observed sequences under the constraint that each sequence is generated i.i.d by a distinct distribution is considered. The number of distributions, and hence the number of…

Information Theory · Computer Science 2018-10-16 Sara Shahi , Daniela Tuninetti , Natasha Devroye

Universal compression of patterns of sequences generated by independently identically distributed (i.i.d.) sources with unknown, possibly large, alphabets is investigated. A pattern is a sequence of indices that contains all consecutive…

Information Theory · Computer Science 2016-11-17 Gil I. Shamir

We study the entropy rate of pattern sequences of stochastic processes, and its relationship to the entropy rate of the original process. We give a complete characterization of this relationship for i.i.d. processes over arbitrary…

Information Theory · Computer Science 2007-07-13 George M. Gemelos , Tsachy Weissman

This paper addresses the question of the fluctuations of the empirical entropy of a chain of infinite order. We assume that the chain takes values on a finite alphabet and loses memory exponentially fast. We consider two possible…

Statistical Mechanics · Physics 2007-05-23 D. Gabrielli , A. Galves , D. Guiol

Stochastic blockmodels are generative network models where the vertices are separated into discrete groups, and the probability of an edge existing between two vertices is determined solely by their group membership. In this paper, we…

Statistical Mechanics · Physics 2013-11-12 Tiago P. Peixoto

The entropy of network ensembles characterizes the amount of information encoded in the network structure, and can be used to quantify network complexity, and the relevance of given structural properties observed in real network datasets…

Disordered Systems and Neural Networks · Physics 2014-06-18 Kartik Anand , Dimitri Krioukov , Ginestra Bianconi

This article investigates integer sequences that partition the sequence into blocks of various lengths - irregular arrays. The main result of the article is explicit formulas for numbering of irregular arrays. A generalization of Cantor…

Combinatorics · Mathematics 2023-10-31 Boris Putievskiy

A permutation $\sigma$ describing the relative orders of the first $n$ iterates of a point $x$ under a self-map $f$ of the interval $I=[0,1]$ is called an \emph{order pattern}. For fixed $f$ and $n$, measuring the points $x\in I$ (according…

Combinatorics · Mathematics 2010-03-30 Aaron Abrams , Eric Babson , Henry Landau , Zeph Landau , James Pommersheim

In this paper we show how the cross-disciplinary transfer of techniques from Dynamical Systems Theory to Number Theory can be a fruitful avenue for research. We illustrate this idea by exploring from a nonlinear and symbolic dynamics…

Number Theory · Mathematics 2018-02-26 Lucas Lacasa , Bartolo Luque , Ignacio Gómez , Octavio Miramontes

The topic of this paper is the distributed and incremental generation of long executions of concurrent systems, uniformly or more generally with weights associated to elementary actions. Synchronizing sequences of letters on alphabets…

Formal Languages and Automata Theory · Computer Science 2017-04-27 Samy Abbes

In this paper we investigate a quantity called conditional entropy of ordinal patterns, akin to the permutation entropy. The conditional entropy of ordinal patterns describes the average diversity of the ordinal patterns succeeding a given…

Chaotic Dynamics · Physics 2014-07-22 Anton M. Unakafov , Karsten Keller

The entropy of a hierarchical network topology in an ensemble of sparse random networks with "hidden variables" associated to its nodes, is the log-likelihood that a given network topology is present in the chosen ensemble.We obtain a…

Disordered Systems and Neural Networks · Physics 2009-11-13 Ginestra Bianconi , Anthony C. C. Coolen , Conrad J. Perez Vicente

Entropy and differential entropy are important quantities in information theory. A tractable extension to singular random variables-which are neither discrete nor continuous-has not been available so far. Here, we present such an extension…

Information Theory · Computer Science 2017-01-04 Günther Koliander , Georg Pichler , Erwin Riegler , Franz Hlawatsch

Labeled infinite trees provide combinatorial interpretations for many integer sequences generated by nested recurrence relations. Typically, such sequences are monotone increasing. Several of these sequences also have straightforward…

Combinatorics · Mathematics 2022-11-07 Nathan Fox

The ordinal patterns of a fixed number of consecutive values in a time series is the spatial ordering of these values. Counting how often a specific ordinal pattern occurs in a time series provides important insights into the properties of…

Statistics Theory · Mathematics 2025-02-06 Annika Betken , Giorgio Micali , Johannes Schmidt-Hieber

Over the past few decades, there has been extensive research on scattered subspaces, partly because of their link to MRD codes. These subspaces can be characterized using linearized polynomials over finite fields. Within this context,…

Combinatorics · Mathematics 2024-02-26 D. Bartoli , A. Giannoni , G. Marino

Consider the set of all sequences of $n$ outcomes, each taking one of $m$ values, that satisfy a number of linear constraints. If $m$ is fixed while $n$ increases, most sequences that satisfy the constraints result in frequency vectors…

Information Theory · Computer Science 2016-11-18 Kostas N. Oikonomou , Peter D. Grunwald

The minimum average number of bits need to describe a random variable is its entropy, assuming knowledge of the underlying statistics On the other hand, universal compression supposes that the distribution of the random variable, while…

Information Theory · Computer Science 2014-04-02 Maryam Hosseini , Narayana Santhanam
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