Neil Gershenfeld. Information in dynamics. In Doug Matzke, editor, Proceedings of the Workshop on Physics of Computation, Dallas, Texas, 1993. IEEE Press. Home/Search Document Details and Download
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Statistical Mechanics and Information Theory - Gunawardena (1995) (Correct)
....model can attain. We apply variants of the hidden Markov models used in speech research to a synthetic detection problem, and we obtain performance that surpasses the theoretical limits for linear models. KS entropy estimates suggest that still better performance is possible. For references, see [31, 32, 33]. Practical Entropy Computation in Complex Systems Neil Gershenfeld, MIT Media Lab neilg media.mit.edu I will discuss the interplay between entropy production in complex systems and the estimation of entropy from observed signals. Entropy measurement in lag spaces provides a very general way to ....
....difficult to do reliably. I will consider the role of regularized density estimation and sorting on adaptive trees in determining entropy from measurements, and then look at applications in nonlinear instrumentation and the optimization of information processing systems. For references, see [33, 79]. Origin and growth of order in the expanding universe David Layzer, Harvard layzer cfa.harvard.edu I define order as potential statistical entropy: the amount by which the entropy of a statistical description falls short of its maximum value subject to appropriate constraints. I argue that, as a ....
N. Gershenfeld. Information in dynamics. In Workshop on Physics and Computation: PhysComp92, pages 276--280. IEEE Computer Society, 1992.
State Reconstruction for Determining Predictability in Driven.. - Schoner (1996) (Correct)
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Neil Gershenfeld. Information in dynamics. In Doug Matzke, editor, Proceedings of the Workshop on Physics of Computation, Dallas, Texas, 1993. IEEE Press.
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