| Paper: | SAM-P7.5 | ||
| Session: | Applications of Multichannel Signal Processing | ||
| Time: | Thursday, May 20, 13:00 - 15:00 | ||
| Presentation: | Poster | ||
| Topic: | Sensor Array and Multichannel Signal Processing: Inverse methods | ||
| Title: | DIVERSITY MEASURE MINIMIZATION BASED METHOD FOR COMPUTING SPARSE SOLUTIONS TO LINEAR INVERSE PROBLEMS WITH MULTIPLE MEASUREMENT VECTORS | ||
| Authors: | Bhaskar Rao; University of California, San Diego | ||
| Kjersti Engan; Stavanger University College | |||
| Shane Cotter; University of California, San Diego | |||
| Abstract: | We address the problem of finding sparse solutions to linear inverse problems when there are Multiple Measurement Vectors (MMV) and the solutions are assumed to have a common, but unknown, sparsity profile. This is an important extension to the single measurement sparse solution problem that has been extensively studied in the past. Of particular interest are methods based on minimizing diversity measures. A measure appropriate for the multiple measurement problem is developed, and an algorithm is derived based on its minimization. The algorithm developed, M-FOCUSS, generalizes the FOcal Underdetermined System Solver (FOCUSS) algorithm developed for the single measurement case. The convergence of the algorithm is established and a simulation study is conducted to evaluate its effectiveness. The results clearly show the ability of M-FOCUSS to utilize multiple measurement vectors to accurately identify the sparsity structure and compute sparse solutions. | ||
| Back | |||
Home -||-
Organizing Committee -||-
Technical Committee -||-
Technical Program -||-
Plenaries
Paper Submission -||-
Special Sessions -||-
ITT -||-
Paper Review -||-
Exhibits -||-
Tutorials
Information -||-
Registration -||-
Travel Insurance -||-
Housing -||-
Workshops