Mathematical Analysis of Large Data Sets

Monday, January 30, 2006, 3:40 p.m. PSA 113

Douglas Cochran

Fulton School of Engineering, ASU

Integration of Sensing and Processing

Abstract The prevailing trend in gathering data with sensors is to convert analog information into digital form as early as possible in the processing chain. This results in huge digital data sets that are often sparse in information that is actually useful. This talk will present general approaches, emerging technologies, and some mathematical ideas for reducing the volume of digital data produced by sensor systems by increasing the information-richness of the data as part of the sensing and digitizing processes.

For further information please contact: Anne Gelb