3,886 research outputs found
Synchronization and Control in Intrinsic and Designed Computation: An Information-Theoretic Analysis of Competing Models of Stochastic Computation
We adapt tools from information theory to analyze how an observer comes to
synchronize with the hidden states of a finitary, stationary stochastic
process. We show that synchronization is determined by both the process's
internal organization and by an observer's model of it. We analyze these
components using the convergence of state-block and block-state entropies,
comparing them to the previously known convergence properties of the Shannon
block entropy. Along the way, we introduce a hierarchy of information
quantifiers as derivatives and integrals of these entropies, which parallels a
similar hierarchy introduced for block entropy. We also draw out the duality
between synchronization properties and a process's controllability. The tools
lead to a new classification of a process's alternative representations in
terms of minimality, synchronizability, and unifilarity.Comment: 25 pages, 13 figures, 1 tabl
Complexity-entropy causality plane: a useful approach for distinguishing songs
Nowadays we are often faced with huge databases resulting from the rapid
growth of data storage technologies. This is particularly true when dealing
with music databases. In this context, it is essential to have techniques and
tools able to discriminate properties from these massive sets. In this work, we
report on a statistical analysis of more than ten thousand songs aiming to
obtain a complexity hierarchy. Our approach is based on the estimation of the
permutation entropy combined with an intensive complexity measure, building up
the complexity-entropy causality plane. The results obtained indicate that this
representation space is very promising to discriminate songs as well as to
allow a relative quantitative comparison among songs. Additionally, we believe
that the here-reported method may be applied in practical situations since it
is simple, robust and has a fast numerical implementation.Comment: Accepted for publication in Physica
Characterization of DNA methylation as a function of biological complexity via dinucleotide inter-distances
We perform a statistical study of the distances between successive
occurrencies of a given dinucleotide in the DNA sequence for a number of
organisms of different complexity. Our analysis highlights peculiar features of
the dinucleotide CG distribution in mammalian DNA, pointing towards a
connection with the role of such dinucleotide in DNA methylation. While the CG
distributions of mammals exhibit exponential tails with comparable parameters,
the picture for the other organisms studied (e.g., fish, insects, bacteria and
viruses) is more heterogeneous, possibly because in these organisms DNA
methylation has different functional roles. Our analysis suggests that the
distribution of the distances between dinucleotides CG provides useful insights
in characterizing and classifying organisms in terms of methylation
functionalities.Comment: 13 pages, 5 figures. To be published in the Philosophical
Transactions A theme issue "DNA as information
Permutation entropy and its main biomedical and econophysics applications: a review
Entropy is a powerful tool for the analysis of time series, as it allows describing the probability distributions of the possible state of a system, and therefore the information encoded in it. Nevertheless, important information may be codified also in the temporal dynamics, an aspect which is not usually taken into account. The idea of calculating entropy based on permutation patterns (that is, permutations defined by the order relations among values of a time series) has received a lot of attention in the last years, especially for the understanding of complex and chaotic systems. Permutation entropy directly accounts for the temporal information contained in the time series; furthermore, it has the quality of simplicity, robustness and very low computational cost. To celebrate the tenth anniversary of the original work, here we analyze the theoretical foundations of the permutation entropy, as well as the main recent applications to the analysis of economical markets and to the understanding of biomedical systems.Facultad de IngenierĂ
Classification and Verification of Online Handwritten Signatures with Time Causal Information Theory Quantifiers
We present a new approach for online handwritten signature classification and
verification based on descriptors stemming from Information Theory. The
proposal uses the Shannon Entropy, the Statistical Complexity, and the Fisher
Information evaluated over the Bandt and Pompe symbolization of the horizontal
and vertical coordinates of signatures. These six features are easy and fast to
compute, and they are the input to an One-Class Support Vector Machine
classifier. The results produced surpass state-of-the-art techniques that
employ higher-dimensional feature spaces which often require specialized
software and hardware. We assess the consistency of our proposal with respect
to the size of the training sample, and we also use it to classify the
signatures into meaningful groups.Comment: Submitted to PLOS On
Information Extraction, Data Integration, and Uncertain Data Management: The State of The Art
Information Extraction, data Integration, and uncertain data management are different areas of research that got vast focus in the last two decades. Many researches tackled those areas of research individually. However, information extraction systems should have integrated with data integration methods to make use of the extracted information. Handling uncertainty in extraction and integration process is an important issue to enhance the quality of the data in such integrated systems. This article presents the state of the art of the mentioned areas of research and shows the common grounds and how to integrate information extraction and data integration under uncertainty management cover
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