The 2007 IEEE Workshop on Statistical Signal Processing is tentatively planned for August 26-29, 2007, at the beautiful Monona Terrace Convention Center in Madison, Wisconsin. The purpose of this workshop is to bring together researchers and scientists from the IEEE Signal Processing Society and related fields, for a two-and-one-half-day workshop focused on statistical methods in signal and image processing. The workshop will feature regular contributed paper sessions, special invited paper sessions, and a small number of plenary lectures covering basic theory, methods and algorithms, and applications in statistical signal processing. Areas of interest include array processing, telecommunications, distributed signal processing and networks, biosignal processing and bioinformatics, Monte Carlo methods, statistical image analysis, and machine learning.
One of the themes to be highlighted in the 2007 IEEE SSP Workshop is the theory and applications of the compressed sensing, and the role that compressed sensing can play in signal analysis and processing. Compressed Sensing was first proposed in 2004 by Professor Emmanuel Candes of Caltech. Candes, who received the National Science Board's prestigious Alan T. Waterman Award for his work, will present a one hour plenary lecture on this subject at the workshop. The workshop will provide an ideal forum for researchers to exchange ideas and relate research progress in this and other emerging areas of vital importance.
