Event Detail

Event Type: 
Probability Seminar
Thursday, October 25, 2007 - 06:30
Covell 221

Speaker Info

School of Electrical Engineering and Computer Science, Oregon State University

Sophisticated multi-dimensional sensors are becoming more commonplace in radar, sonar, ultrasound medical imaging, and seismic signal collection systems. Statistical signal processing of acquired data from the sensors involves multi-dimensional and multi-channel (multivariate) covariance matrix structures for purposes of detection and target/feature classification. The size of matrices in actual sensor applications have dimensions of many thousands and require fast computational algorithms to make them feasible for real-time implementation. This presentation will show the some fast algorithm structures involving parametric means of estimating the covariances for the one-dimensional case to establish a baseline, and then will show some recent research efforts to develop the two-dimensional versions dealing with doubly Toeplitz (or Toeplitz-block-Toeplitz in some literature) structures.