Mixed H2/H-infinity Approach to Robust Estimation and Adaptive Filtering

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9529325 Kailath The project has two different but related objectives. The first is the study of mixed H-2/H-inf control and estimation problems; the second is to develop new software that will enable graduate students and researchers to run realistic projects that will call upon them to synthesize knowledge from different areas of statistical signal processing and numerical analysis. Classical H-2 methods (such as Wiener filtering and Kalman filtering) require knowledge of second-order statistics of the exogeneous signals and yield estimators that have best average performance. On the other hand, the more recent H-inf (or so called minimax) estimation methods require no statistical knowledge of the exogeneous signals and yield conservative solutions. The major goals of this proposal are (1) to develop, as completely as possible, an analytical characterization of the solution of mixed H-2/H-inf problem, (2) to obtain a through understanding of the tradeoffs between the average and worst-case performances, (3) to seek recursive implementations of the optimal, (4) to provide efficient numerical algorithms. ***