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Immersion Into Noise

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Book Series: Critical Climate Change ISBN: 9781607852414 Year: Language: English
Publisher: Open Humanities Press
Subject: Agriculture (General) --- Social Sciences --- Science (General)
Added to DOAB on : 2012-04-06 14:37:34
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Joseph Nechvatal's Immersion Into Noise investigates multiple aspects of cultural noise by applying our audio understanding of noise to the visual, architectual and cognative domains. The author takes the reader through phenomenal aspects of the art of noise into algorithmic and network contexts, beginning in the Abside of the Grotte de Lascaux.

Error-Correction Coding and Decoding: Bounds, Codes, Decoders, Analysis and Applications

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Book Series: Signals and Communication Technology ISSN: 1860-4862 / 1860-4870 ISBN: 9783319511023 9783319511030 Year: Pages: 522 DOI: 10.1007/978-3-319-51103-0 Language: English
Publisher: Springer
Subject: Computer Science --- Media and communication
Added to DOAB on : 2017-03-31 15:07:50
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This book discusses both the theory and practical applications of self-correcting data, commonly known as error-correcting codes. The applications included demonstrate the importance of these codes in a wide range of everyday technologies, from smartphones to secure communications and transactions. Written in a readily understandable style, the book presents the authors’ twenty-five years of research organized into five parts:Part I is concerned with the theoretical performance attainable by using error correcting codes to achieve communications efficiency in digital communications systems.Part II explores the construction of error-correcting codes and explains the different families of codes and how they are designed. Techniques are described for producing the very best codes.Part III addresses the analysis of low-density parity-check (LDPC) codes, primarily to calculate their stopping sets and low-weight codeword spectrum which determines the performance of these codes.Part IV deals with decoders designed to realize optimum performance.Part V describes applications which include combined error correction and detection, public key cryptography using Goppa codes, correcting errors in passwords and watermarking.This book is a valuable resource for anyone interested in error-correcting codes and their applications, ranging from non-experts to professionals at the forefront of research in their field.

Probabilistic Framework for Sensor Management

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Book Series: Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Universität Karlsruhe, Intelligent Sensor-Actuator-Systems Laboratory ISSN: 18673813 ISBN: 9783866444058 Year: Volume: 7 Pages: VI, 159 p. DOI: 10.5445/KSP/1000012224 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Computer Science
Added to DOAB on : 2019-07-30 19:59:17
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A probabilistic sensor management framework is introduced, which maximizes the utility of sensor systems with many different sensing modalities by dynamically configuring the sensor system in the most beneficial way. For this purpose, techniques from stochastic control and Bayesian estimation are combined such that long-term effects of possible sensor configurations and stochastic uncertainties resulting from noisy measurements can be incorporated into the sensor management decisions.

Information Decomposition of Target Effects from Multi-Source Interactions

Authors: --- --- ---
ISBN: 9783038970156 9783038970163 Year: Pages: 336 DOI: 10.3390/books978-3-03897-016-3 Language: englisch
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Mathematics --- Physics (General)
Added to DOAB on : 2018-09-04 13:22:10
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Using Shannon information theory to analyse the contributions from two source variables to a target, for example, we can measure the information held by one source about the target, the information held by the other source about the target, and the information held by those sources together about the target. Intuitively, however, there is strong desire to measure further notions of how this directed information interaction may be decomposed, e.g., how much information the two source variables hold redundantly about the target, how much each source variable holds uniquely, and how much information can only be discerned by synergistically examining the two sources together.The absence of measures for such decompositions into redundant, unique and synergistic information is arguably the most fundamental missing piece in classical information theory. Triggered by the formulation of the Partial Information Decomposition framework by Williams and Beer in 2010, the past few years have witnessed a concentration of work by the community in proposing, contrasting, and investigating new measures to capture these notions of information decomposition.This Special Issue seeks to bring together these efforts, to capture a snapshot of the current research, as well as to provide impetus for and focused scrutiny on newer work, present progress to the wider community and attract further research. Our contributions present: several new approaches for measures of such decompotions; commentary on properties, interpretations and limitations of such approaches; and applications to empirical data (in particular to neural data).

New Trends in Statistical Physics of Complex Systems

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ISBN: 9783038974697 / 9783038974703 Year: Pages: 202 DOI: 10.3390/books978-3-03897-470-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Mathematics --- Physics (General)
Added to DOAB on : 2019-01-28 09:04:46
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A topical research activity in statistical physics concerns the study of complex and disordered systems. Generally, these systems are characterized by an elevated level of interconnection and interaction between the parts so that they give rise to a rich structure in the phase space that self-organizes under the control of internal non-linear dynamics. These emergent collective dynamics confer new behaviours to the whole system that are no longer the direct consequence of the properties of the single parts, but rather characterize the whole system as a new entity with its own features, giving rise to the birth of new phenomenologies. As is highlighted in this collection of papers, the methodologies of statistical physics have become very promising in understanding these new phenomena. This volume groups together 12 research works showing the use of typical tools developed within the framework of statistical mechanics, in non-linear kinetic and information geometry, to investigate emerging features in complex physical and physical-like systems.A topical research activity in statistical physics concerns the study of complex and disordered systems. Generally, these systems are characterized by an elevated level of interconnection and interaction between the parts so that they give rise to a rich structure in the phase space that self-organizes under the control of internal non-linear dynamics. These emergent collective dynamics confer new behaviours to the whole system that are no longer the direct consequence of the properties of the single parts, but rather characterize the whole system as a new entity with its own features, giving rise to the birth of new phenomenologies. As is highlighted in this collection of papers, the methodologies of statistical physics have become very promising in understanding these new phenomena. This volume groups together 12 research works showing the use of typical tools developed within the framework of statistical mechanics, in non-linear kinetic and information geometry, to investigate emerging features in complex physical and physical-like systems.

Information-based methods for neuroimaging: analyzing structure, function and dynamics

Authors: --- ---
Book Series: Frontiers Research Topics ISSN: 16648714 ISBN: 9782889195022 Year: Pages: 191 DOI: 10.3389/978-2-88919-502-2 Language: English
Publisher: Frontiers Media SA
Subject: Neurology --- Science (General)
Added to DOAB on : 2015-12-03 13:02:24
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The aim of this Research Topic is to discuss the state of the art on the use of Information-based methods in the analysis of neuroimaging data. Information-based methods, typically built as extensions of the Shannon Entropy, are at the basis of model-free approaches which, being based on probability distributions rather than on specific expectations, can account for all possible non-linearities present in the data in a model-independent fashion.Mutual Information-like methods can also be applied on interacting dynamical variables described by time-series, thus addressing the uncertainty reduction (or information) in one variable by conditioning on another set of variables.In the last years, different Information-based methods have been shown to be flexible and powerful tools to analyze neuroimaging data, with a wide range of different methodologies, including formulations-based on bivariate vs multivariate representations, frequency vs time domains, etc. Apart from methodological issues, the information bit as a common unit represents a convenient way to open the road for comparison and integration between different measurements of neuroimaging data in three complementary contexts: Structural Connectivity, Dynamical (Functional and Effective) Connectivity, and Modelling of brain activity. Applications are ubiquitous, starting from resting state in healthy subjects to modulations of consciousness and other aspects of pathophysiology.Mutual Information-based methods have provided new insights about common-principles in brain organization, showing the existence of an active default network when the brain is at rest. It is not clear, however, how this default network is generated, the different modules are intra-interacting, or disappearing in the presence of stimulation. Some of these open-questions at the functional level might find their mechanisms on their structural correlates. A key question is the link between structure and function and the use of structural priors for the understanding of the functional connectivity measures. As effective connectivity is concerned, recently a common framework has been proposed for Transfer Entropy and Granger Causality, a well-established methodology originally based on autoregressive models. This framework can open the way to new theories and applications.This Research Topic brings together contributions from researchers from different backgrounds which are either developing new approaches, or applying existing methodologies to new data, and we hope it will set the basis for discussing the development and validation of new Information-based methodologies for the understanding of brain structure, function, and dynamics.

On the Beneficence of Censorship

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Book Series: Arbeiten und Texte zur Slavistik ISBN: 9783876902111 Year: Pages: 286 Language: English
Publisher: Peter Lang International Academic Publishing Group
Added to DOAB on : 2019-01-15 13:32:00
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Lev Loseff (1937), der Leningrad 1976 verlassen musste und seit 1979 in Hannover, New Hampshire am Dartmouth College in den USA als Professor of Russian Language and Literature lehrt, hat u.a. Werke von E. Švarc, N. Olejnikov und M. Bulgakov herausgegeben. In seiner ersten großen Monographie "On the Beneficence of Censorship: Aesopian Language in Modern Russian Literature" analysiert Loseff an Werken von Švarc, Solženicyn, Evtušenko u.a. die aus der Auseinandersetzung mit der Zensur gebotenen stilistischen - auch bereichernden - Besonderheiten der modernen, in der Sowjetunion entstandenen russischen Literatur und veranschaulicht diese im Kontext von Werk, Autor und Epoche.

Information Theory in Neuroscience

Authors: ---
ISBN: 9783038976646 Year: Pages: 280 DOI: 10.3390/books978-3-03897-665-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Mathematics --- Science (General)
Added to DOAB on : 2019-03-21 15:50:41
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As the ultimate information processing device, the brain naturally lends itself to being studied with information theory. The application of information theory to neuroscience has spurred the development of principled theories of brain function, and has led to advances in the study of consciousness, as well as to the development of analytical techniques to crack the neural code—that is, to unveil the language used by neurons to encode and process information. In particular, advances in experimental techniques enabling the precise recording and manipulation of neural activity on a large scale now enable for the first time the precise formulation and the quantitative testing of hypotheses about how the brain encodes and transmits the information used for specific functions across areas. This Special Issue presents twelve original contributions on novel approaches in neuroscience using information theory, and on the development of new information theoretic results inspired by problems in neuroscience.

Biological Information:New Perspectives

Authors: --- --- --- --- et al.
ISBN: 9789814508728 Year: Pages: 584 DOI: 10.1142/8818 Language: English
Publisher: World Scientific Publishing Co.
Subject: Technology (General)
Added to DOAB on : 2016-01-19 03:49:23
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In the spring of 2011, a diverse group of scientists gathered at Cornell University to discuss their research into the nature and origin of biological information. This symposium brought together experts in information theory, computer science, numerical simulation, thermodynamics, evolutionary theory, whole organism biology, developmental biology, molecular biology, genetics, physics, biophysics, mathematics, and linguistics. This volume presents new research by those invited to speak at the conference.The contributors to this volume use their wide-ranging expertise in the area of biological information to bring fresh insights into the many explanatory difficulties associated with biological information. These authors raise major challenges to the conventional scientific wisdom, which attempts to explain all biological information exclusively in terms of the standard mutation/selection paradigm.Several clear themes emerged from these research papers: 1) Information is indispensable to our understanding of what life is; 2) Biological information is more than the material structures that embody it; 3) Conventional chemical and evolutionary mechanisms seem insufficient to fully explain the labyrinth of information that is life. By exploring new perspectives on biological information, this volume seeks to expand, encourage, and enrich research into the nature and origin of biological information.Contents:Session One — Information Theory & Biology: Introductory Comments (Robert J Marks II):Biological Information — What is It? (Werner Gitt, Robert Compton and Jorge Fernandez)A General Theory of Information Cost Incurred by Successful Search (William A Dembski, Winston Ewert and Robert J Marks II)Pragmatic Information (John W Oller, Jr)Limits of Chaos and Progress in Evolutionary Dynamics (William F Basener)Tierra: The Character of Adaptation (Winston Ewert, William A Dembski and Robert J Marks II)Multiple Overlapping Genetic Codes Profoundly Reduce the Probability of Beneficial Mutation (George Montañez, Robert J Marks II, Jorge Fernandez and John C Sanford)Entropy, Evolution and Open Systems (Granville Sewell)Information and Thermodynamics in Living Systems (Andy C McIntosh)Session Two — Biological Information and Genetic Theory: Introductory Comments (John C Sanford):Not Junk After All: Non-Protein-Coding DNA Carries Extensive Biological Information (Jonathan Wells)Can Purifying Natural Selection Preserve Biological Information? (Paul Gibson, John R Baumgardner, Wesley H Brewer and John C Sanford)Selection Threshold Severely Constrains Capture of Beneficial Mutations (John C Sanford, John R Baumgardner and Wesley H Brewer)Using Numerical Simulation to Test the “Mutation-Count” Hypothesis (Wesley H Brewer, John R Baumgardner and John C Sanford)Can Synergistic Epistasis Halt Mutation Accumulation? Results from Numerical Simulation (John R Baumgardner, Wesley H Brewer and John C Sanford)Computational Evolution Experiments Reveal a Net Loss of Genetic Information Despite Selection (Chase W Nelson and John C Sanford)Information Loss: Potential for Accelerating Natural Genetic Attenuation of RNA Viruses (Wesley H Brewer, Franzine D Smith and John C Sanford)DNA.EXE: A Sequence Comparison between the Human Genome and Computer Code (Josiah Seaman)Biocybernetics and Biosemiosis (Donald Johnson)Session Three — Theoretical Molecular Biology: Introductory Comments (Michael J Behe):An Ode to the Code: Evidence for Fine-Tuning in the Standard Codon Table (Jed C Macosko and Amanda M Smelser)A New Model of Intracellular Communication Based on Coherent, High-Frequency Vibrations in Biomolecules (L Dent)Getting There First: An Evolutionary Rate Advantage for Adaptive Loss-of-Function Mutations (Michael J Behe)The Membrane Code: A Carrier of Essential Biological Information That is Not Specified by DNA and is Inherited Apart from It (Jonathan Wells)Explaining Metabolic Innovation: Neo-Darwinism Versus Design (Douglas D Axe and Ann K Gauger)Session Four — Biological Information and Self-Organizational Complexity Theory: Introductory Comments (Bruce L Gordon):Evolution Beyond Entailing Law: The Roles of Embodied Information and Self Organization (Stuart Kauffman)Towards a General Biology: Emergence of Life and Information from the Perspective of Complex Systems Dynamics (Bruce H Weber)Readership: Academics, researchers, postgraduates and advanced undergraduates in bioinformatics. Biologists, mathematicians/statisticians, physicists and computer scientists.

Complexity, Criticality and Computation (C³)

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ISBN: 9783038425144 9783038425151 Year: Pages: VI, 262 DOI: 10.3390/books978-3-03842-515-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Physics (General)
Added to DOAB on : 2017-10-02 11:37:22
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Complex systems is a new approach to science, engineering, health and management that studies how relationships between parts give rise to the collective emergent behaviours of the entire system, and how the system interacts with its environment.A system can be thought of as complex if its dynamics cannot be easily predicted, or explained, as a linear summation of the individual dynamics of its components. In other words, the many constituent microscopic parts bring about macroscopic phenomena that cannot be understood by considering a single part alone (“the whole is more than the sum of the parts”). There is a growing awareness that complexity is strongly related to criticality: the behaviour of dynamical spatiotemporal systems at an order/disorder phase transition where scale invariance prevails.Complex systems can also be viewed as distributed information-processing systems. Consciousness emerging from neuronal activity and interactions, cell behaviour resultant from gene regulatory networks and swarming behaviour are all examples of global system behaviour emerging as a result of the local interactions of the individuals (neurons, genes, animals). Can these interactions be seen as a generic computational process? This question shapes the special issue, linking computation to complexity and criticality.

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