 Maximum entropy spectral estimation

The maximum entropy method applied to spectral density estimation. The overall idea is that the maximum entropy rate stochastic process that satisfies the given constant autocorrelation and variance constraints, is a linear GaussMarkov process with i.i.d. zeromean, Gaussian input.
Contents
Method description
The maximum entropy rate, strongly stationary stochastic process x_{i} with autocorrelation sequence satisfying the constraints:
 R_{xx}(k) = α_{k}
for arbitrary constants α_{k} is the Pth order, linear Markov chain of the form:
where the y_{i} are zero mean, i.i.d. and normallydistributed of finite variance σ^{2}.
Spectral estimation
Given the a_{k}, the square of the absolute value of the transfer function of the linear Markov chain model can be evaluated at any required frequency in order to find the power spectrum of x_{i}.
References
 Cover, T. and Thomas, J. (1991) Elements of Information Theory, John Wiley and Sons, Inc.
External links
 kSpectra Toolkit for Mac OS X from SpectraWorks.
Categories: Entropy
 Information theory
 Signal processing
 Time series analysis
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