New LS and SVD based methods for estimating frequencies of complex sinusoids
New least squares (LS) and singular value decomposition (SVD) based methods for the estimation of frequencies of complex sinusoids in white noise are presented. The methods are based on a new prediction problem that has some very useful properties leading to algorithms that have considerably reduced complexity. This is achieved without the sacrifice of any significant measure of performance with respect to existing methods that are based on the forward-backward predictor.<<ETX>>