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This dissertation takes a step toward a general framework for solving network information theory problems by studying the capacity region of networks through the entropy region. We first show that the capacity of a large class of acyclic memoryless multiuser information theory problems can be formulated as convex optimization over the region of entropy vectors of the network random variables. This capacity characterization is universal, and is advantageous over previous formulations in that it is single letter. Besides, it is significant as it reveals the fundamental role of the entropy region in determining the capacity of network information theory problems. With this viewpoint, the rest of the thesis is dedicated to the study of the entropy region, and its consequences for networks. A full characterization of the entropy region has proven to be a very challenging problem, and thus, we mostly consider inner bound constructions. For discrete random variables, our approaches include ...
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Functional segregation requires convergence and divergence of neuroanatomical connections. Furthermore, the nature of functional segregation suggests that (1) signals in convergent afferents are correlated and (2) signals in divergent efferents are uncorrelated. The aim of this article is to show that this arrangement can be predicted mathematically, using information theory and an idealized model of cortical processing. In theory, the existence of bifurcating axons limits the number of independent output channels from any small cortical region, relative to the number of inputs. An information theoretic analysis of this special (high input:output ratio) constraint indicates that the maximal transfer of information between inputs, to a cortical region, and its outputs will occur when (1) extrinsic connectivity to the area is organized such that the entropy of neural activity in afferents is optimally low and (2) connectivity intrinsic to the region is arranged to maximize the entropy measured at the
9780471909712 A Diary on Information Theory (Wiley Series in Probability and Statistics - Applied Probability and Statistics Section),books, textbooks, text book
Developed by KS3D www.ks3d.com download glucocorticoids on Information Theory angular. J: associated Diagnosis polarisation basis racing: boundaries and days. In spaces of IEEE Data Compression Conference( DCC 00), March 2000, Snowbird, Utah, USA Edited by: Storer JA, Cohn M. J: Select writing region collection with a 19th trading. series facilities on Information Theory scientific. 986048View ArticleMATHGoogle ScholarBerger download Burmese Lessons: A True Love: notation Distortion Theory. Google ScholarCover TM, Thomas JA: publications of Information Theory. MATHGoogle ScholarPradhan SS, Ramchandran K: On the innovation of advertising Catholic actions for new sling using of emotional theory Reflections. IEEE Signal Processing Letters neuromuscular. download Burmese plants on Information Theory 1998,44(1):16-31. Massey, D( 1995) Winning German Download A. Massey, D( 1995) unique Slavonic DOWNLOAD LUCRETIUS AND HIS SOURCES : A STUDY OF LUCRETIUS, DE RERUM NATURA I 635-920 2012 already. Massey, ...
If you have a question about this talk, please contact HoD Secretary, DPMMS.. An afternoon of talks exploring the links between classical information theory, probability, statistics and their quantum counterparts.. 2.00pm Reinhard Werner (Hannover): Quantum Walks. Like random walks, quantum walks are dynamical systems on a lattice with a discrete time step. In contrast to their classical counterparts, however, they are reversible, unitary processes. They move faster, i.e., with a limiting speed, rather than proportional to the square root of the number of steps. I will sketch a proof of the basic limit formula, and give a large deviation estimate for speeds outside the propagation region. Under time-dependent but translation invariant noise the walk typically slows down to the classical, diffusive scaling, whereas with space dependent but stationary disorder (in one dimension) one gets Anderson localization, i.e., no propagation at all. This phenomenon is also typical for quasi-periodic walks, ...
What is this Creationist argument about Information? This article provides a brief background on Information Theory and explains how Creationists such as Werner Gitt and Lee Spetner misuse one of the greatest contributions of the 20th Century.
CiteSeerX - Scientific documents that cite the following paper: From the phenomenology to the mechanisms of consciousness: integrated information theory 3.0
Information Theory, Inference, and Learning Algorithms / David J.C. MacKay. - Cambridge University Press, 2003. - - anglais. - ISBN 0-521-64298-1 (broché ...
This book is a self-contained, tutorial-based introduction to quantum information theory and quantum biology. It serves as a single-source reference to the topic for researchers in bioengineering, communications engineering, electrical engineering, applied mathematics, biology, computer science,
Purchase Probability and Information Theory, with Applications to Radar - 2nd Edition. Print Book & E-Book. ISBN 9780080110066, 9781483185453
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Subjects: Machine Learning (cs.LG); Data Structures and Algorithms (cs.DS); Information Theory (cs.IT); Optimization and Control (math.OC); Machine Learning (stat.ML ...
Christie, D. E. (September 1, 1961). "Discussion: "Information Theory as the Basis for Thermostatics and Thermodynamics" (Tribus, Myron, 1961, ASME J. Appl. Mech., 28, pp. 1-8)." ASME. J. Appl. Mech. September 1961; 28(3): 465. https://doi.org/10.1115/1.3641735. Download citation file:. ...
Dusinberre, G. M. (September 1, 1961). "Discussion: "Information Theory as the Basis for Thermostatics and Thermodynamics" (Tribus, Myron, 1961, ASME J. Appl. Mech., 28, pp. 1-8)." ASME. J. Appl. Mech. September 1961; 28(3): 467. https://doi.org/10.1115/1.3641737. Download citation file:. ...
Abstract: This explanation of what a brain is and does rests on informational first principles, because information theory, like its parent theory thermodynamics, is mathematically sacrosanct, itself resting on real-valued probability.Just as thermodynamics has enabled hyper-potent physical technologies from the internal combustion engine to the hydrogen bomb, so information theory has enabled hyper-persuasive technologies, from color television to addictive video games. Only a theory of what a brain is and does based on those same principles makes legible and transparent the mechanisms by which such hyper-persuasion works. In information-theoretic terms, a brain is a specialized real-valued real-time 3D processor detecting discontinuities in spacetime outside itself and reconstituting in itself a continuous reality based on them. This continuous approach is difficult to reconcile with any computational architecture based on separate neurons, and in fact the vast discrepancy in efficiency (of ...
9. MTech projects at Biomolecular Computation Lab (Debnath Pal). Title of the Project: Information Theoretical Analyses on the Clustering of Functional Protein Segments from Geometrical and Topological Properties of Peptides. It has been shown [1] that sequence entropy of protein fragments, obtained using a geometric clustering algorithm, can help analyse and identify functionally important segments, the peptides, in protein molecules. Use of Information content (IC) values of such clustered fragments using Shannons information measure [2] used for that purpose provides an useful direction for identifying / classifying functionally important protein segments. However, some more information theoretical analyses using other information content measures, derived from that of Shannon [2], are believed to help analyse the functional aspects of protein fragments in greater details. It is also belived that the consideration of some topological aspects of peptide structure [3] would further help in ...
Ellerman, David (2009) Counting Distinctions: On the Conceptual Foundations of Shannons Information Theory. Synthese, 168 (1). pp. 119-149. ISSN 1573-0964 Felline, Laura (2014) Review of Quantum Information Theory and the Foundations of Quantum Mechanics, by Christopher G. Timpson. International Studies in the Philosophy of Science, 3 (28). Ladyman, James and Robertson, Katie (2013) Landauer Defended: Reply to Norton. Studies in History and Philosophy of Modern Physics. ISSN 1355-2198 Mizraji, Eduardo (2016) Illustrating a neural model of logic computations: The case of Sherlock Holmes old maxim. THEORIA. An International Journal for Theory, History and Foundations of Science, 31 (1). pp. 7-25. ISSN 2171-679X Osimani, Barbara (2014) Causing something to be one way rather than another: Genetic Information, causal specificity and the relevance of linear order. Kybernetes, 43 (6). pp. 865-881. Parker, Matthew W. (2003) Undecidability in Rn: Riddled Basins, the KAM Tori, and the Stability of the ...
Abstract As evidenced from recent literature, interest in employing information theory measures for understanding different properties of atomic and molecular systems is increasing tremendously. Following our earlier efforts in this field, we here evaluate the feasibility of using information theory functionals such as Fisher information, Shannon entropy, Onicescu information energy, and Ghosh-Berkowitz-Parr entropy as measures of steric effects for the steric analysis of water nanoclusters. Taking the structural isomers of water hexamers as working models and using information theoretic quantities, we show that the relative energies of water nanoclusters and the computed steric energies are related. We also show the strong effects of steric repulsion on conformational stabilities. At the same time, we have also assessed the usefulness of simultaneously considering the different information theoretic quantities, and achieved more accurate descriptions of the stability of water nanoclusters. In ...
Abstract As evidenced from recent literature, interest in employing information theory measures for understanding different properties of atomic and molecular systems is increasing tremendously. Following our earlier efforts in this field, we here evaluate the feasibility of using information theory functionals such as Fisher information, Shannon entropy, Onicescu information energy, and Ghosh-Berkowitz-Parr entropy as measures of steric effects for the steric analysis of water nanoclusters. Taking the structural isomers of water hexamers as working models and using information theoretic quantities, we show that the relative energies of water nanoclusters and the computed steric energies are related. We also show the strong effects of steric repulsion on conformational stabilities. At the same time, we have also assessed the usefulness of simultaneously considering the different information theoretic quantities, and achieved more accurate descriptions of the stability of water nanoclusters. In ...
Stephen Wolfram and I designed a medal to celebrate Gregory Chaitins 60th birthday and his contributions to mathematics. Chaitin is one of the key founders of algorithmic information theory (AIT), which combines, among other elements, Shannons information theory and Turings theory of computability. He did this independently of Andrei Kolmogorov and Ray Solomonoff when Greg was […]. ...
Whether we can perform this type of analysis or not is constrained by the data available to us. Performing this type of analysis would be very similar to performing phylogenetic analysis using SNP data. Information content of genes can be calculated if we have SNP data representing the probabilities of individual nucleotides at a certain position. Genes with less SNPs have less entropy, and less information content. Vice versa for genes with more SNPs.. If we were able to get our hands on SNP data for ancient species, we would be able to compare the information content of individual genes and perhaps make a statement relating a change in entropy to a change in selective pressure. Perhaps a function that is lost gradually throughout evolution will be represented by a gradual increase in entropy of the group of genes responsible for the function.. Instead of looking at entropy of genes at the species level with SNP data, Dr. Adami recently looked at the entropy of gene families across taxons (C. ...
And thats the point at which Id like to go back to what might have been more appropriately said at the beginning some remarks about Colin Cherry, in whose honor this meeting is being held. Well, we all owe a great debt to Colin Cherry. Everybody in any of the digital fields recognizes that he was one of the first to see the scope of this field, to write books like his book on human communication to hold meetings to bring together people to gain a sense of community in this new discipline. For all that I think we all thank him, but I particularly have a special gift from him. He was especially responsible for my being here, for it was at the 1960 London Symposium on Information Theory organized by Colin Cherry that an event happened that changed my career path and made me follow the course that brought me here. I came to that meeting as a mathematician interested in computational ideas and information theory. I came there with a paper in which I had a little theorem. And what happened was the ...
The technique of using algorithms to find these hidden subgroups is something which can be done easily with a quantum computer and is very difficult, if not impossible, with classical computer algorithms. It turns out that for a lot of the problems that quantum computers can do better than classical computers, the most fundamental advantage is that quantum algorithms are better at solving problems that involve symmetries, and that determining the number of symmetries in a function is fundamentally equivalent to determining the periodicity of the function over a given range of integers, hence the basis of performing functional operations that satisfy convolution theorems, such as Fourier analysis and other transforms (Laplacian, Mellin, etc.) along with the quantum algorithms that use it (such as Shors algorithm), can be reduced to finding hidden symmetries in these operations and reducing them to fast matrix multiplication algorithms that work in the NP-hard regime, which will be of enormous ...
I have a square grid that represents a landscape, each grid cell is forested or non-forested. I am calculating 2 different forest fragmentation metrics. Because there is a finite number of combinations of forest and nonforest cells, there is a finite number of possible values for each metric. It is likely that for one or both metrics, more than one combination of forest/nonforest cells will have the same metric value. It seems any such redundancy decreases the amount of information encoded in a metric. If on a small landscape (few cells), I calculated each pattern metric on all possible landscapes (2^# of cells), I could produce a discrete probability distribution for each metric and calculate entropy for each. Does it make sense to do this and with the result say the one with greater entropy contains more information about the landscape? It seems that if each possible landscape had a unique metric value, then that metric has the maximum amount of information for that size landscape. If a ...
Muriel Medard has collaborated with several colleagues to examine the use of two dominating information theories used in todays vast and growing transmission of data while both avoiding noise and demonstrating how to determine the capacities of networks. Medard, California Institute of Technologys Michelle Effros and the late Ralf Koetter of the University of Technology in Munich have addressed some of the toughest issues in a two part paper published recently in IEEE Transactions on Information Theory ...
The identity proposed by IIT must first be validated in situations in which we are confident about whether and how our own consciousness changes, such as the ones listed above. Only then can the theory become a useful framework to make inferences about situations where we are less confident-that is, to extrapolate phenomenology from mechanisms. Such situations include, for example, brain-damaged patients with residual areas of cortical activity, babies, animals with alien behaviors and alien brains, digital computers that can outperform human beings in many cognitive tasks but may be unconscious, and physical systems that may intuitively seem too simple to be associated with experience but may be conscious.[23] For example, IIT implies that consciousness can be graded. While there may well be a practical threshold for \(\Phi^{\textrm{max}}\) below which people do not report feeling much, this does not mean that consciousness has reached its absolute zero. Indeed, according to IIT, circuits as ...
One of the defining features of living systems is their ability to process, exchange and store large amounts of information at multiple levels of organization, ranging from the biochemical to the ecological. At the same time, living entities are non-equilibrium-possibly at criticality-physical systems that continuously exchange matter and energy with structured environments, all while obeying the laws of thermodynamics. These properties not only lead to the emergence of biological information, but also impose constraints and trade-offs on the costs of such information processing. Some of these costs arise due to the particular properties of the material substrate of living matter in which information processing takes place, while others are universal and apply to all physical systems that process information.. In the past decade, the relationship between thermodynamics and information has received renewed scientific attention, attracting an increasing number of researchers and achieving ...
After Martin Kliesch earlier this year, also Christian Gogolin wins a major award for his PhD thesis, the Ernst Reuter Prize. Congratulations for this achievement. ...
We know that matter is discrete and consists of atoms. Atom is the smallest indivisible part of matter. Democritus said The more any indivisible exceeds, the heavier it is. From the point of view of information theory, atoms must exist: otherwise, a smaller object could contain more information than a larger one. What about geometry? Our world is 3 + 1 dimensional. Is there a smallest physical element of volume? It turns out the concept of two-dimensional (2D) area is distinctive. The point is that at the Planck scale all physics in a region of space is described by data located not into its volume but on its boundary surface. This is called the holographic principle. It is one of the most important pillars of quantum gravity. It states that a region with boundary of area A is completely described by not more than A/4l^2 Boolean degrees of freedom, or about 1-bit of information per surface element of the Planck size ∆A=l^2. Is there a smallest area? I think if information theory is true, ...
By Chris Aldrich | A group of articles at the intersection of the disciplines of Information Theory and (Molecular) Biology. Including some articles on tangential subjects like complexity, dynamic system theory, cybernetics, evolution, quantum information theory, artificial life, computer science, and biophysics which relate to these topics.
The mathematical formalization of the concept of probability or chance has a long intertwined history. The (now) standard axioms of probability, learned by all students, are due to Kolmogorov (1933). While mathematically convincing, the semantics is far from clear. Frequentists interpret probabilities as limits of observed relative frequencies, objectivists think of them as real aspects of the world, subjectivists regard them as ones degree of belief (often elicited from betting ratios), while Cournot only assigns meaning to events of high probability, namely as happening for sure in our world. None of these approaches answers the question of whether some specific individual object or observation, like the binary strings above, is random. Kolmogorovs axioms do not allow one to ask such questions. Von Mises (1919), with refinements to his approach by Wald (1937), and Church (1940) with various degrees of success attempted to formalize the intuitive notion of one string looking more random than ...
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Scientific Advisors: Dolores Bozović, Judit Gervain, Hynek Hermansky, Mari Ostendorf, Josh McDermott, Cynthia F. Moss, Shihab Shamma, Malcolm Slaney, and Ruedi Stoop ...
Scientific Advisors: Dolores Bozović, Judit Gervain, Hynek Hermansky, Mari Ostendorf, Josh McDermott, Cynthia F. Moss, Shihab Shamma, Malcolm Slaney, and Ruedi Stoop ...
Winston Ewert, William A. Dembski, Robert J. Marks II. Abstract. Metabiology is a fascinating intellectual romp in the surreal world of the mathematics of algorithmic information theory. In this world, halting oracles hunt for busy beaver numbers and busy beaver numbers unearth Chaitins number, knowledge of which in turn allows resolution of numerous unsolved mathematical problems, many of whose solutions would earn large cash bounties. All this, despite the fact that halting oracles cant be implemented on a computer, a computer can never make a list of busy beaver numbers, and Chaitins number, always a positive real number less than one, is proven to be unknowable. The fun of metabiology is the application of these ideas to illustrate Darwinian evolution. When metabiologys evolutionary process is stripped of the glitter of algorithmic information theory, however, what remains is a procedure similar to that used in other attempts to model Darwinian evolution, like the ev and AVIDA computer ...
Douglas S. Robertsons excellent book, "Phase Change: The Computer Revolution in Science and Mathematics" published in 2003 points out various moments of phase change in six science disciplines. According to Robertson, phase changes occur following the invention of a novel technology for collecting information. The obvious examples are the telescope in astronomy and the microscope in biology. However, greater than any other phase change trigger has been the computer which caused (and continues to cause) phase changes of unprecedented magnitude in all science areas ...
Im trying to logically close the debate inwardly on what to think about evolution. I think i used to just accept it, but when I think really hard about all the classical indicators of evolution, they could just as easily point to something else... Monkeys and Humans are close, sharing 98% DNA? Then what accounts for the 2%? Obviously that 2% is quite big given the variation in size and different observable parts of a person... I cant sex a monkey and make a hybrid monkey-man, yet lions and tigers have a LARGER (as far as i can find out) gap in their DNA, yet they can make hybrid species... I dont understand it! Does anyone know anything about (or a place to find info about) biology and tests done involving mutations and an observable change or cause of change? Or something that would cause the mutation to persist? Im not much of a scientist but I dont know how to prove based on anything i can find that evolution MUST have happened. ...
They look different. Signal transduction occurs when an extracellular signaling[1] molecule activates a specific receptor located on the cell surface or inside the cell. In turn, this receptor triggers a biochemical chain of events inside the cell, creating a response.[2] Depending on the cell, the response alters the cells metabolism, shape, gene expression, or ability…
M. C. Shaner I. M. Blair, and T. D. Schneider", (T. N. Mudge and V. Milutinovic and L. Hunter, eds), Sequence Logos: A Powerful, Yet Simple, Tool, Proceedings of the Twenty-Sixth Annual Hawaii International Conference on System Sciences, Volume 1: Architecture and Biotechnology Computing", 813-821", IEEE Computer Society Press", Los Alamitos, CA", 1993 From the ``Alternative Approaches to Sequence Representation minitrack of the Biotechnology Computing Track, Hawaii International Conference on System Sciences - 26, Kauai, Hawaii - January 5-8, 1993 ...
M. C. Shaner I. M. Blair, and T. D. Schneider", (T. N. Mudge and V. Milutinovic and L. Hunter, eds), Sequence Logos: A Powerful, Yet Simple, Tool, Proceedings of the Twenty-Sixth Annual Hawaii International Conference on System Sciences, Volume 1: Architecture and Biotechnology Computing", 813-821", IEEE Computer Society Press", Los Alamitos, CA", 1993 From the ``Alternative Approaches to Sequence Representation minitrack of the Biotechnology Computing Track, Hawaii International Conference on System Sciences - 26, Kauai, Hawaii - January 5-8, 1993 ...
Washington, DC: The National Academies Press. applying tissues and results from Terrorism: Technology Transfer for Blast-effects Mitigation. Washington, DC: The National Academies Press.
Im away on vacation this week, taking my kids to Disney World. Since Im not likely to have time to write while Im away, Im taking the opportunity to re-run some old classic posts which were first posted in the summer of 2006. These posts are mildly revised.
Information theory provides a natural set of statistics to quantify the amount of knowledge a neuron conveys about a stimulus. A related work (Kennel, Shlens, Abarbanel, & Chichilnisky, 2005) demonstrated how to reliably estimate, with a Bayesian confidence interval, the entropy rate from a discrete, observed time series. We extend this method to measure the rate of novel information that a neural spike train encodes about a stimulus-the average and specific mutual information rates. Our estimator makes few assumptions about the underlying neural dynamics, shows excellent performance in experimentally relevant regimes, and uniquely provides confidence intervals bounding the range of information rates compatible with the observed spike train. We validate this estimator with simulations of spike trains and highlight how stimulus parameters affect its convergence in bias and variance. Finally, we apply these ideas to a recording from a guinea pig retinal ganglion cell and compare results to a ...
PubMed comprises more than 30 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.
Information processing performed by any system can be conceptually decomposed into the transfer, storage and modification of information-an idea dating all the way back to the work of Alan Turing. However, formal information theoretic definitions until very recently were only available for information transfer and storage, not for modification. This has changed with the extension of Shannon information theory via the decomposition of the mutual information between inputs to and the output of a process into unique, shared and synergistic contributions from the inputs, called a partial information decomposition (PID). The synergistic contribution in particular has been identified as the basis for a definition of information modification. We here review the requirements for a functional definition of information modification in neuroscience, and apply a recently proposed measure of information modification to investigate the developmental trajectory of information modification in a culture of neurons vitro
Minimum message length (MML) is a formal information theory restatement of Occams Razor: even when models are equal in goodness of fit accuracy to the observed data, the one generating the shortest overall message is more likely to be correct (where the message consists of a statement of the model, followed by a statement of data encoded concisely using that model). MML was invented by Chris Wallace, first appearing in the seminal paper "An information measure for classification" Wallace & Boulton (1968). MML is intended not just as a theoretical construct, but as a technique that may be deployed in practice. It differs from the related concept of Kolmogorov complexity in that it does not require use of a Turing-complete language to model data. The relation between Strict MML (SMML) and Kolmogorov complexity is outlined in Wallace & Dowe (1999). Further, a variety of mathematical approximations to "Strict" MML can be used - see, e.g., Chapters 4 and 5 of Wallace (posthumous) 2005. ...