Title :
The total variance of a periodogram-based spectral estimate of a stochastic process with spectral uncertainty and its application to classifier design
Author :
Zhang, Yanwu ; Baggeroer, Arthur B. ; Bellingham, James G.
Author_Institution :
Monterey Bay Aquarium Res. Inst., Moss Landing, CA, USA
Abstract :
The variance of a spectral estimate of a stochastic process is essential to the formulation and performance of a spectral classifier. The overall variance of a spectral estimate originates from two sources: the within-class spectral uncertainty and the variance introduced in the spectral estimation procedure. In this paper, we derive the total variance of a periodogram-based spectral estimate under some assumptions. Using this result, we formulate a linear spectral classifier based on Fisher´s separability metric. The classifier is used to classify two oceanographic processes: ocean convection versus internal waves.
Keywords :
convection; ocean waves; oceanographic techniques; signal classification; stochastic processes; Fisher separability metric; classifier design; internal waves; ocean convection; oceanographic process; periodogram-based spectral estimate variance; spectral uncertainty; stochastic process; within-class spectral uncertainty; Analysis of variance; Classification tree analysis; Fourier transforms; Frequency estimation; Helium; Linear systems; Oceans; Smoothing methods; Stochastic processes; Uncertainty; Classifier; periodogram; spectral uncertainty;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2005.859346
