| Paper: | MLSP-P4.2 | ||
| Session: | Audio and Communication Applications | ||
| Time: | Thursday, May 18, 14:00 - 16:00 | ||
| Presentation: | Poster | ||
| Topic: | Machine Learning for Signal Processing: Blind Signal Separation and Independent Component Analysis | ||
| Title: | An Adaptive Paraunitary Approach For Blind Equalization of All Equalizable MIMO Channels | ||
| Authors: | Alper Erdogan, Koç University, Turkey | ||
| Abstract: | We introduce a novel adaptive paraunitary approach to be used for the blind deconvolution of all deconvolvable MIMO mixing systems with memory. The proposed adaptive approach is based on the use of alternating projections technique for the enforcement of the paraunitary constraint. The use of this approach enables extension of various instantaneous Blind Source Separation (BSS) approaches to handle the convolutive BSS case. Three such methods, namely FastICA, Multi User Kurtosis and BSS for Bounded Magnitude signals are provided to illustrate the use of this approach. | ||
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