In many real-world scenarios, different source signals are mixed in a dispersive environment, and there is significant interest to separate the sources solely on the basis of the observed mixtures, without prior knowledge of the sources or the mixing system. A well-known example is a cocktail party situation, where many people are speaking at the same time in a reverberant room, and a listener has to separate out the signal of interest. Other applications of blind source separation include the ecg analysis of mother and fetus, fMRI data analysis, image restoration, and digital communications over multipath channels. In this project, we aim at finding technical solutions for the separation of sounds in acoustic reverberant environments solely on the basis of observed microphone signals. The project has been funded by the German Research Foundation (DFG).

Radoslaw Mazur, Tiemin Mei, Alfred Mertins

A CUDA Implementation of Independent Component Analysis in the Time-Frequency Domain:

### 2013

Nov 2013

Mazur, R., Jungmann, J. O., and Mertins, A.:

**A new clustering approach for solving the permutation problem in convolutive blind source separation**. Proc. Workshop on Applications of Signal Processing to Audio and
Acoustics (WASPAA), New Paltz, USA, Oct. 2013

Okt 2013

Mazur, R., Jungmann, J. O., and Mertins, A.:

**Optimized Dyadic Sorting for Solving the Permutation Ambiguity in
Acoustic Blind Source Separation**. Proc. European Signal Processing Conference, Marrakech, Maroc, Sept 2013

Mär 2013

Mazur, R., Jungmann, J. O., and Mertins, A.:

**A Curtosis Based Criterion for Solving the Permutation Ambiguity in Convolutive Blind Source Separation**. Proc. AIA-DAGA 2013 Conference on Acoustics, Merano, Italy, pp. 187-188, Mar. 2013

### 2012

Mär 2012

Mazur, R., Jungmann, J. O., and Mertins, A.:

**Optimized Gradient Calculation for Room Impulse Response Reshaping Algorithm Based on p-Norm Optimization**. Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing, Kyoto, Japan, pp. 185-188, Mar. 2012

### 2011

Jul 2011

Mazur, R. and Mertins, A.:

**A CUDA Implementation of Independent Component Analysis in the Time-Frequency
Domain**. Proc. European Signal Processing Conference, Barcelona, Spain, pp. 512-514, Aug 2011

Mai 2011

Mazur, R. and Mertins, A.:

**A Sparsity Based Criterion for Solving the Permutation Ambiguity
in Convolutive Blind Source Separation**. Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing, Prague, Czech Republic, pp. 1996-1999, May 2011

### 2010

Sep 2010

Mazur, R. and Mertins, A.:

**A Method for Filter Equalization in Convolutive Blind Source Separation**. Proc. 9th Int. Conf. on Latent Variable Analysis and Signal Separation, St. Malo, France, Sept. 2010

Aug 2010

Mazur, R. and Mertins, A.:

**Improving the Robustness of the Correlation Approach for Solving
the Permutation Problem in the Convolutive Blind Source Separation**. Proc. International Workshop on Acoustic Echo and Noise control (IWAENC), Tel Aviv, Israel, Aug. 2010

### 2009

Aug 2009

Mazur, R. and Mertins, A.:

**Simplified Formulation of a Depermutation Criterion in Convolutive
Blind Source Separation**. Proc. European Signal Processing Conference, Glasgow, Scotland, pp. 1467-1470, Aug 2009

Apr 2009

Mazur, R. and Mertins, A.:

**Using the scaling ambiguity for filter shortening in convolutive
blind source separation**. Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing, Taipei, Taiwan, pp. 1709-1712, April 2009

Mär 2009

Mazur, R. and Mertins, A.:

**A Method for Filter Shaping in Convolutive Blind Source Separation**. Independent Component Analysis and Signal Separation (ICA2009), Springer, LNCS, vol. 5441, pp. 282-289, 2009

Jan 2009

Mazur, R. and Mertins, A.:

**An Approach for Solving the Permutation Problem of Convolutive Blind Source Separation based on Statistical Signal Models**.

*IEEE Trans. Audio, Speech, and Language Processing*, vol. 17, no. 1, pp. 117--126, Jan. 2009

### 2008

Nov 2008

Mei, T. and Mertins, A.:

**Convolutive Blind Source Separation Based on Disjointness Maximization of Subband Signals**.

*IEEE Signal Processing Letters*, vol. 15, pp. 725-728, 2008

Okt 2008

Mazur, R. and Mertins, A.:

**On Separation Performance Enhancement in Convolutive Blind Source
Separation**. Proc. Asilomar Conference on Signals, Systems, and Computers, pp. 1718-1721, Oct. 2008

Jul 2008

Mei, T., Mertins, A., and Yin, F.:

**On the Generalization of Blind Source Separation
Algorithms from Instantaneous to Convolutive Mixtures**. Proc. IEEE sensor array and multi-channel signal processing workshop
(SAM2008), Darmstadt, pp. 482-486, July 2008

Jan 2008

Mei, T., Mertins, A., Yin, F., Xi, J., and Chicharo, J. F.:

**Blind Source Separation for Convolutive Mixtures Based on the Joint
Diagonalization of Power Spectral Density Matrices**.

*Signal Processing*, vol. 88, no. 8, pp. 1990--2007, 2008

### 2007

Sep 2007

Mazur, R. and Mertins, A.:

**Solving the Permutation Problem in Convolutive Blind Source Separation**. Independent Component Analysis and Signal Separation, Davies, M. E., James, C. J., Abdallah, S. A., and Plumbley, M. D. (Ed.), Springer, LNCS, vol. 4666, pp. 512-519, 2007

### 2006

Nov 2006

Mei, T., Xi, J., Yin, F., Mertins, A., and Chicharo, J. F.:

**Blind Source Separation Based on Time-domain Optimizations of a Frequency-domain Independence Criterion**:

IEEE Trans. Audio Speech and Language Processing, Nov. 2006

Sep 2006

Mazur, R. and Mertins, A.:

**Reducing reverberation effects in convolutive blind source separation**:

*Proc. European Signal Processing Conference*, Florence Italy, Sept. 2006

### 2005

Aug 2005

Mei, T., Yin, F., Xi, J., and Chicharo, a. . A. M. J. F.:

**A half-frequency domain approach for convolutive blind source separation based on Kullback-Leibler divergence**. Proc. of the Eighth Int. Symposium on Signal Processing and Its Applications, Sydney, Australia, vol. 1, pp. 25-28, Aug. 2005