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Antisparsity as a Prior in Blind Separation of Correlated Sources
  • Renan Brotto ,
  • Kenji Nose-Filho ,
  • João M. T. Romano
Renan Brotto
University of Campinas

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Kenji Nose-Filho
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João M. T. Romano
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Abstract

This letter introduces the concept of antisparse Blind Source Separation (BSS), proposing a suitable criterion based on the $\ell_\infty$ norm to explore the antisparsity feature.
The effectiveness of the criterion is theoretically demonstrated and it is also evaluated by computational simulations, which consider up to ten distinct sources with different correlation levels. Moreover, we simulated a scenario in wireless communication with binary sources, comparing our approach to the Constant Modulus algorithm. Both the theoretical and the simulation results highlight the potentiality of using antisparsity as a prior in BSS.