Fast Computational Methods and Subspace Algebra in Signal Processing Algorithms and Implementations

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The research activity in this project will utilize concepts of linear matrix algebra to design fast computational algorithms for signal processing. In the last decade, concepts from linear matrix algebra have acquired a central position in the development of signal processing algorithms. The solution to many practical signal processing problems can be obtained in terms of ranks of certain matrices and corresponding subspaces. In fact, the importance of subspaces in signal processing is motivation for developing tools from the algebra of subspaces, multilinear algebra. Some important application areas for linear and multilinear algebra include direction of arrival estimation, frequency estimation, signal detection, seismic and geological exploration, dynamic analysis of structures, biomedical signal processing, system identification, chemistry and economics.