Titlebook: Maximum Entropy and Bayesian Methods; Seattle, 1991 C. Ray Smith,Gary J. Erickson,Paul O. Neudorfer Book 1992 Springer Science+Business Med

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CHART

Unmixing Mineral Spectra Using a Neural Net with Maximum Entropy Regularization,ral exploration, the number of spectral values measured [the pattern features] is substantially less than the number of possible constituent minerals and the unmixing problem is under determined. These two techniques were used to unmix . 24-channel imaging spectrometer data and a Thematic Mapper [TM

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安抚

Book 1992e usefully treated by these methods, and manyareas of theoretical research are being enhanced by the thoughtfulapplication of Bayes‘ theorem. The contributions contained in thisvolume present a state-of-the-art review that will be influential anduseful for many years to come. .

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0168-1222 . The contributions contained in thisvolume present a state-of-the-art review that will be influential anduseful for many years to come. .978-90-481-4220-0978-94-017-2219-3Series ISSN 0168-1222 Series E-ISSN 2365-6425

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健谈

0168-1222 he revolution in computational methods afforded by moderncomputers, allow astronomers, electrical engineers, image processorsof any type, NMR chemists and physicists, and anyone at all who has todeal with incomplete and noisy data, to take advantage of methodsthat, in the past, have been applied onl

SMART

Linking the Plausible and Demonstrative Inferences,and demonstrative patterns is shown. The plausible and demonstrative elementary patterns are expressed by logic equations which are exactly complementary. This complementarity condition determines the linking form between all the plausible and demonstrative patterns derived from the elementary patterns.

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Maximum Likelihood Estimation of the Lagrange Parameters of the Maximum Entropy Distributions,the ML method for this problem. Finally, we show the interest of these developpements in determining the prior law of an image in a Bayesian approach to solving the inverse problems of image restoration and reconstruction.