Results 231 to 240 of about 559,544 (282)
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Statistica Neerlandica, 1984
AbstractMaximum entropy or minumum information distributions have their flexibilities severely curtailed if R or R+ is the domain and α is imposed as a Lebesgue measure. Tremendous flexibility is gained by removing these restrictions.
Mukherjee, D., Hurst, D. C.
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AbstractMaximum entropy or minumum information distributions have their flexibilities severely curtailed if R or R+ is the domain and α is imposed as a Lebesgue measure. Tremendous flexibility is gained by removing these restrictions.
Mukherjee, D., Hurst, D. C.
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Applied Optics, 1986
In this paper we discuss the use of the maximum entropy principle in tomographic reconstruction. We emphasize that entropy maximization is the only consistent regularization technique for images. A method of encoding prior information is discussed, and an example of the use of prior knowledge in the restoration of a fuel pin bundle is given.
S F, Gull, T J, Newton
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In this paper we discuss the use of the maximum entropy principle in tomographic reconstruction. We emphasize that entropy maximization is the only consistent regularization technique for images. A method of encoding prior information is discussed, and an example of the use of prior knowledge in the restoration of a fuel pin bundle is given.
S F, Gull, T J, Newton
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IEEE Transactions on Information Theory, 1993
Summary: Burg's standard maximum entropy method and the resulting autoregressive model has been widely applied for spectrum estimation and prediction. A generalization of the maximum entropy formalism in a nonparametric setting is presented, and the class of the resulting solutions is identified to be a class of Markov processes.
Politis, Dimitris Nicolas +1 more
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Summary: Burg's standard maximum entropy method and the resulting autoregressive model has been widely applied for spectrum estimation and prediction. A generalization of the maximum entropy formalism in a nonparametric setting is presented, and the class of the resulting solutions is identified to be a class of Markov processes.
Politis, Dimitris Nicolas +1 more
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Maximum entropy Tokamak configurations
Plasma Physics and Controlled Fusion, 1990The new entropy concept for the collective magnetic equilibria developed in preceding papers is applied to the description of the states of a Tokamak subjected to Ohmic and auxiliary heating. The condition of existence of steady-state plasmas with vanishing entropy production implies, on the one hand, the resilience of specific current density profiles
E Minardi, G Lampis
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Maximum Entropy Image Reconstruction
IEEE Transactions on Computers, 1977Two-dimensional digital image reconstruction is an important imaging process in many of the physical sciences. If the data are insufficient to specify a unique reconstruction, an additional criterion must be introduced, either implicitly or explicitly before the best estimate can be computed. Here we use a principle of maximum entropy, which has proven
Wernecke, Stephen J. +1 more
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Maximum dynamic entropy models
Journal of Applied Probability, 2004A formal approach to produce a model for the data-generating distribution based on partial knowledge is the well-known maximum entropy method. In this approach, partial knowledge about the data-generating distribution is formulated in terms of some information constraints and the model is obtained by maximizing the Shannon entropy under these ...
Asadi, Majid +3 more
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2020
Abstract A major goal of ecology is to predict patterns and changes in the abundance, distribution, and energetics of individuals and species in ecosystems. The maximum entropy theory of ecology (METE) predicts the functional forms and parameter values describing the central metrics of macroecology, including the distribution of ...
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Abstract A major goal of ecology is to predict patterns and changes in the abundance, distribution, and energetics of individuals and species in ecosystems. The maximum entropy theory of ecology (METE) predicts the functional forms and parameter values describing the central metrics of macroecology, including the distribution of ...
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Constrained Maximum-Entropy Sampling
Operations Research, 1998A fundamental experimental design problem is to select a most informative subset, having prespecified size, from a set of correlated random variables. Instances of this problem arise in many applied domains such as meteorology, environmental statistics, and statistical geology.
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Operations Research, 2006 This paper presents a method to assign utility values when only partial information is available about the decision maker’s preferences. We introduce the notion of a utility density function and a maximum entropy principle for utility assignment. The maximum entropy utility solution embeds a large family of utility functions that includes the most ...
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