A novel data-adaptive power spectrum estimation technique

In this paper a novel data adaptive power spectrum estimation procedure is introduced. This estimate, called PSEUDA for Power Spectrum Estimation Using Data Adaptation, unifies under one conceptual framework the Autoregressive or Maximum Entropy Method (MEM) and the Maximum Likelihood Method (MLM) by providing a method which is continuosly variable between these two extremes For small bandwidths the results obtained are similar to the Data Adaptive Spectral Estimate (DASE) introduced by Davis and Regier [4]. Unlike DASE, a fast algorithm has been developed for the PSEUDA estimate. This algorithm consist of three parts: 1) a Levinsion recursion, 2) a weighted correlation of the prediction error coefficients obtained in step one, and 3) the use of an FFT to calculate the estimate of the spectrum.