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Recently an instantaneous blind source separation (BSS) approach that exploits the bounded magnitude structure of digital communications signals has been introduced. In this paper, we introduce a deflationary adaptive algorithm based on this criterion and provide its convergence analysis. We show that the resulting algorithm is convergent to one of the globally optimal points that correspond to perfect separation. The simulation examples related to the separation of digital communication signals are provided to illustrate the convergence and the performance of the algorithm [ABSTRACT FROM PUBLISHER]

We approach the multiple input multiple output (MIMO) decision feedback equalization (DFE) problem in digital communications from an H∞ estimation point of view. Using the standard (and simplifying) assumption that all previous decisions are correct, we obtain an explicit parameterization of all H∞ optimal DFEs. In particular, we show that, under the above assumption, minimum mean square error (MMSE) DFEs are H∞ optimal. The H∞ approach also suggests a method for dealing with errors in previous decisions. [ABSTRACT FROM AUTHOR]