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Analysis of the variance threshold of Kay's weighted linear predictor frequency estimator

A theoretical approximation for the variance of Kay's weighted linear predictor frequency estimator is derived. From this expression, an inequality describing the variance threshold of the estimator is found. The window weights are then optimized to improve the variance. Numerical simulations demonstrate that the variance approximations are valid for medium to high signal-to-noise ratios or for large numbers of samples. >