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State-Space Architecture of the Partitioned-Block-Based Acoustic Echo Controller

: Kuech, Fabian; Mabande, Edwin; Enzner, Gerald


Institute of Electrical and Electronics Engineers -IEEE-; IEEE Signal Processing Society:
IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2014. Vol.2 : Florence, Italy, 4 - 9 May 2014
Piscataway, NJ: IEEE, 2014
ISBN: 978-1-4799-2894-1
ISBN: 978-1-4799-2892-7
ISBN: 978-1-4799-2893-4
International Conference on Acoustics, Speech and Signal Processing (ICASSP) <39, 2014, Florence>
Conference Paper
Fraunhofer IIS ()

Acoustic echo cancellation has traditionally employed basically all variants known from deterministic adaptive filter design, such as least mean-square (LMS), recursive least-squares (RLS), and frequency-domain adaptive filters (FDAF). More recently, a stochastic adaptive filter design based on the concept of acoustic state-space modeling of the echo path has been introduced to accommodate for an ever sought unification of adaptive filtering and adaptation control. The corresponding Kalman filter theory has been formulated for single-channel, multi-channel, and nonlinear echo cancellation problems. This paper closes an important gap by formulating the state-space model and the corresponding adaptive algorithm for the partitioned-block filtering structure which is especially relevant in practice. This structure allows for the use of significantly longer filter lengths in comparison to previous work, and for the flexible design and implementation of acoustic echo cancellers for widely differing acoustic conditions.