P. Bornmann, T. Hemsel, W. Sextro, T. Maeda, and T. Morita, “Non-perturbing cavitation detection / monitoring in sonochemical reactors,” in Ultrasonics Symposium (IUS), 2012 IEEE International, 2012, pp. 1141–1144.

A. Krueger and R. Haeb-Umbach, “MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 2011, pp. 3596–3599.

A. Krueger, E. Warsitz, and R. Haeb-Umbach, “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 19, no. 1, pp. 206–219, 2011.

A. Krueger and R. Haeb-Umbach, “Model-Based Feature Enhancement for Reverberant Speech Recognition,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 18, no. 7, pp. 1692–1707, 2010.

A.-L. Vollmer et al., “People modify their tutoring behavior in robot-directed interaction for action learning,”10.1109/DEVLRN.2009.5175516__in Development and Learning, 2009. ICDL 2009. IEEE 8th International Conference on Development and Learning, 2009, pp. 1–6, doi:10.1109/DEVLRN.2009.5175516 .

V. Ion and R. Haeb-Umbach, “A Novel Uncertainty Decoding Rule With Applications to Transmission Error Robust Speech Recognition,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 16, no. 5, pp. 1047–1060, 2008.

Y. Vanderperren, W. Müller, and W. Dahaene, “UML for Electronic Systems Design – A Comprehensive Overview,”10.1007/s10617-008-9028-9__Design Automation for Embedded Systems, vol. 12, pp. 261–292, 2008, doi:10.1007/s10617-008-9028-9 .

K. Danne, R. Mühlenbernd, and M. Platzner, “Server-based execution of periodic tasks on dynamically reconfigurable hardware,” IET Computers Digital Techniques, vol. 1, no. 4, pp. 295–302, 2007.

R. Schäfer, W. Müller, R. Deimann, and B. Kleinjohann, “A Low-Cost Positioning System for Location-Aware Applications in Smart Homes,” 2007.

R. Haeb-Umbach, “Automatic generation of phonetic regression class trees for MLLR adaptation,” IEEE Transactions on Speech and Audio Processing, vol. 9, no. 3, pp. 299–302, 2001.