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Revision with unchanged content. This book introduces time-frequency-autoregressive-moving-average (TFARMA) models for underspread nonstationary stochastic processes. TFARMA models are parsimonious as well as physically intuitive and meaningful because they are formulated in terms of time shifts (delays) and Doppler frequency shifts. They are a subclass of the well-known time-varying ARMA models with basis function expansion where the basis function set is given by the complex exponentials. The resulting mathematical structure allows for efficient estimation algorithms.

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received the MSC and PhD degrees in electricalengineering in 2001 and 2006 from ViennaUniversity of Technology. Currently he is workingat Freiburg University on signal processing forneurology. His technical interests are in estimationtheory, multivariate signal analysis, and epilepticseizure prediction.

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