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Solution of Autocorrelation Function Constrained Maximum Entropy Problems Using the Method of Simulated Annealing

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Part of the book series: Fundamental Theories of Physics ((FTPH,volume 36))

Abstract

An algorithm is presented that constrains the autocorrelation function of noise removed when a maximum entropy model of noisy data is selected. The algorithm uses the method of simulated annealing and is applied to a model data set. The algorithm is successful in finding solutions to both unconstrained and constrained maximum entropy problems.

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References

  1. Farrow N.A. and Ottensmeyer F.P.; Image and Signal Processing, Ed. Hawkes P.W., S.E.M. Inc. in print (1987)

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  2. Farrow N.A. and Ottensmeyer F.P., Maximum Entropy and Bayesian Spectral Analysis, Ed. Erickson G.J. and Smith CR., Kluwer Academic Publishing, in print (1987)

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  3. Brian R.K. and Skilling J.; Mon. Not. R. Astr. Soc. (1980) 191, 69–79

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  4. Kirkpatrick, S., Gelatt, C.D., and Vecchi, M.D., 1983 Science, 220, pp 671–680

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© 1989 Springer Science+Business Media Dordrecht

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Farrow, N.A., Ottensmeyer, F.P. (1989). Solution of Autocorrelation Function Constrained Maximum Entropy Problems Using the Method of Simulated Annealing. In: Skilling, J. (eds) Maximum Entropy and Bayesian Methods. Fundamental Theories of Physics, vol 36. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-7860-8_16

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  • DOI: https://doi.org/10.1007/978-94-015-7860-8_16

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-4044-2

  • Online ISBN: 978-94-015-7860-8

  • eBook Packages: Springer Book Archive

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