Learn More
How accurately can deterministic modes be identified from a finite record of noisy data? In this paper we answer this question by computing the Cramer-Rao bound on the error covariance matrix of any unbiased estimator of mode parameters. The bound is computed for many of the standard parametric descriptions of a mode, including autoregressive and moving(More)
—This paper is concerned with the structure of estima-tors of correlation matrices and correlation sequences. We argue that reasonable estimators of the correlation matrix are quadratic in the data and nonnegative definite. We also specify the structure of the estimator when the data are modulated: a property we call modulation covariance. We state a(More)
Cramer-Rao bounds have been previously generalized to the class of nonlinear estimation problems on manifolds. This new approach can be used to derive a broad class of quadratic error performance bounds. A generalized intrinsic score function on the manifold-valued parameter space is introduced that distinguishes one bound from another. The derivation(More)