Maximum Likelihood Covariance Estimation with a Condition Number Constraint

@article{Won2006MaximumLC,
  title={Maximum Likelihood Covariance Estimation with a Condition Number Constraint},
  author={Joong Ho Won and Seung-Jean Kim},
  journal={2006 Fortieth Asilomar Conference on Signals, Systems and Computers},
  year={2006},
  pages={1445-1449}
}
In many signal processing applications, we want to estimate the covariance matrix of a multivariate Gaussian distribution. We often require the estimate to be not only invertible but also well-conditioned. We consider the maximum likelihood estimation of the covariance matrix with a constraint on the condition number. We show that this estimation problem can be reformulated as a convex univariate minimization problem, which admits an analytic solution. This estimation method requires no special… CONTINUE READING
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