Title: Robust Estimation in Signal Processing
Robust statistics continue to gain importance due to an increase of impulsive measurement environments and outliers in practical engineering systems. Classical estimation or detection theory does not apply in such situations and robust statistical methods are sought for. The keynote aims at discussing the most recent advances in robust statistics and at showing their power to solving signal processing problems. First, we highlight the motivation for using robust statistics in real-life situations and how robust statistics can be expected to remedy problems in such practical systems. We then introduce some definitions of robustness and discuss some robust estimators. The theoretical treatment is supported by applications in various areas of signal and antenna array processing.