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Mathematics in Independent Component Analysis

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BIBLIOGRAPHY 305<br />

Taleb, A. and Jutten, C. (1999). Indeterm<strong>in</strong>acy and identifiability of bl<strong>in</strong>d identification. IEEE<br />

Transactions on Signal Process<strong>in</strong>g, 47(10):2807–2820.<br />

Theis, F. (2004a). A new concept for separability problems <strong>in</strong> bl<strong>in</strong>d source separation. Neural<br />

Computation, 16:1827–1850.<br />

Theis, F. (2004b). Uniqueness of complex and multidimensional <strong>in</strong>dependent component analysis.<br />

Signal Process<strong>in</strong>g, 84(5):951–956.<br />

Theis, F. (2004c). Uniqueness of real and complex l<strong>in</strong>ear <strong>in</strong>dependent component analysis<br />

revisited. In Proc. EUSIPCO 2004, pages 1705–1708, Vienna, Austria.<br />

Theis, F. (2005a). Bl<strong>in</strong>d signal separation <strong>in</strong>to groups of dependent signals us<strong>in</strong>g jo<strong>in</strong>t block<br />

diagonalization. In Proc. ISCAS 2005, pages 5878–5881, Kobe, Japan.<br />

Theis, F. (2005b). Gradients on matrix manifolds and their cha<strong>in</strong> rule. Neural Information<br />

Process<strong>in</strong>g LR, 9(1):1–13.<br />

Theis, F. (2005c). Multidimensional <strong>in</strong>dependent component analysis us<strong>in</strong>g characteristic functions.<br />

In Proc. EUSIPCO 2005, Antalya, Turkey.<br />

Theis, F. (2007). Towards a general <strong>in</strong>dependent subspace analysis. In Proc. NIPS 2006.<br />

Theis, F. and Amari, S. (2004). Postnonl<strong>in</strong>ear overcomplete bl<strong>in</strong>d source separation us<strong>in</strong>g sparse<br />

sources. In Proc. ICA 2004, volume 3195 of LNCS, pages 718–725, Granada, Spa<strong>in</strong>. Spr<strong>in</strong>ger.<br />

Theis, F. and García, G. (2006). On the use of sparse signal decomposition <strong>in</strong> the analysis of<br />

multi-channel surface electromyograms. Signal Process<strong>in</strong>g, 86(3):603–623.<br />

Theis, F., Georgiev, P., and Cichocki, A. (2004a). Bl<strong>in</strong>d source recovery: algorithm comparison<br />

and fusion. In Proc. MaxEnt 2004, volume 735 of AIP conference proceed<strong>in</strong>gs, pages 320–327,<br />

Garch<strong>in</strong>g, Germany.<br />

Theis, F., Georgiev, P., and Cichocki, A. (2007a). Robust sparse component analysis based on<br />

a generalized hough transform. EURASIP Journal on Applied Signal Process<strong>in</strong>g.<br />

Theis, F. and Gruber, P. (2005). On model identifiability <strong>in</strong> analytic postnonl<strong>in</strong>ear ICA. Neurocomput<strong>in</strong>g,<br />

64:223–234.<br />

Theis, F., Gruber, P., Keck, I., and Lang, E. (2007b). A robust model for spatiotemporal<br />

dependencies. Neurocomput<strong>in</strong>g (<strong>in</strong> press).<br />

Theis, F., Gruber, P., Keck, I., Meyer-Bäse, A., and Lang, E. (2005a). Spatiotemporal bl<strong>in</strong>d<br />

source separation us<strong>in</strong>g double-sided approximate jo<strong>in</strong>t diagonalization. In Proc. EUSIPCO<br />

2005, Antalya, Turkey.<br />

Theis, F., Gruber, P., Keck, I., Tomé, A., and Lang, E. (2005b). A spatiotemporal second-order<br />

algorithm for fMRI data analysis. In Proc. CIMED 2005, pages 194–201, Lisbon, Portugal.

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