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PHD Exam of Dr.-Ing. Stefan Kühl
Dr.-Ing. Stefan Kühl has successfully completed his oral PHD examination. Dr. Kühl gave an overview of his work about:
"Adaptive Algorithms for the Identification of Time-Variant Acoustic Systems"
Abstract: Many digital speech and audio communication systems incorporate models of acoustic systems during signal processing. Often, the time-variant impulse responses of these acoustic systems have to be identified during or before using a communication system by means of adaptive algorithms.
This thesis compares measurement procedures from the field of acoustics and tracking algorithms from communication applications in a joint mathematical framework, which contributes a novel proof of their mathematical equivalence for periodic excitation, thus helping to bridge the gap between these two closely related fields. It provides insights into the adaptation behavior over time in dependence on the excitation signal used and presents a new multi-channel excitation strategy for continuous system identification based on exponential sweeps.
For acoustic echo cancellation in hands-free calls or teleconferences, acoustic systems have to be tracked with correlated excitation. In this thesis, it is shown how algorithms like the NLMS or RLS algorithm can be derived as constrained versions of a general Kalman filter. For the time-domain Kalman filter, a novel convergence analysis is carried out, showing how correlated excitation affects the adaptation performance. For the frequency-domain Kalman filter, a decorrelation stage is developed, which improves the adaptation performance for correlated excitation.
Furthermore, acquiring multiple channels of an acoustic system simultaneously in order to capture the full sound field offers the potential to provide a more natural sound experience. When dealing with multiple channels, additional aspects and difficulties compared to identifying only one channel arise, which are analyzed in this thesis. Moreover, a reduced-complexity algorithm for spatial audio communication is presented relying on a sparse activity of sound sources.
For many applications, besides the input and output signal, further information is available which can be incorporated in the filter adaptation process as a priori information. This thesis proposes methods to use a priori information for the combination of a beamformer and AEC and for adaptive feedback cancellation as required for IP based teleconferencing.
Overall, this thesis considers the different aspects of system identification of time-variant acoustic systems for diverse scenarios. It provides new insights into the relationship of different system identification algorithms and proposes novel concepts and algorithms for specific applications.