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Notes on maximum-entropy processing (Corresp.)

Julian Edward, Michael M. Fitelson

Open publisher page 102 citations

Abstract

Maximum-entropy processing is a method for computing the power density spectrum from the firstNlags of the autocorrelation function. Unlike the discrete Fourier transform, maximum-entropy processing does not assume that the other lag values are zero. Instead, one mathematically ensures that the fewest possible assumptions about unmeasured data are made by choosing the spectrum that maximizes the entropy for the process. The use of the maximum entropy approach to spectral analysis was introduced by Burg [1]. In this correspondence, the authors derive the maximum-entropy spectrum by obtaining a spectrum that is forced to maximize the entropy of a stationary random process.

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What this paper is about

Maximum-entropy processing is a method for computing the power density spectrum from the firstNlags of the autocorrelation function. Unlike the discrete Fourier transform, maximum-entropy processing does not assume that the other lag values are zero. Instead, one mathematically ensures that the fewest possible assumptions about unmeasured data are made by choosing the spectrum that maximizes the entropy for the process. The use of the maximum entropy approach to spectral analysis was introduced by Burg [1]. In this correspondence, the authors derive the maximum-entropy spectrum by obtaining a spectrum that is forced to maximize the entropy of a stationary random process.

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Available abstract

Maximum-entropy processing is a method for computing the power density spectrum from the firstNlags of the autocorrelation function. Unlike the discrete Fourier transform, maximum-entropy processing does not assume that the other lag values are zero. Instead, one mathematically ensures that the fewest possible assumptions about unmeasured data are made by choosing the spectrum that maximizes the entropy for the process. The use of the maximum entropy approach to spectral analysis was introduced by Burg [1]. In this correspondence, the authors derive the maximum-entropy spectrum by obtaining a spectrum that is forced to maximize the entropy of a stationary random process.

Key concepts: Maximum entropy spectral estimation, Principle of maximum entropy, Autocorrelation, Entropy (arrow of time), Spectral density, Mathematics, Maximum entropy probability distribution, Fourier transform

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