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arxiv: 1609.09744 · v2 · pith:SVR6JNDDnew · submitted 2016-09-30 · 💻 cs.SD · stat.ML

Phase Unmixing : Multichannel Source Separation with Magnitude Constraints

classification 💻 cs.SD stat.ML
keywords multichannelseparationsourceapproachesconvexknownmethodproblem
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We consider the problem of estimating the phases of K mixed complex signals from a multichannel observation, when the mixing matrix and signal magnitudes are known. This problem can be cast as a non-convex quadratically constrained quadratic program which is known to be NP-hard in general. We propose three approaches to tackle it: a heuristic method, an alternate minimization method, and a convex relaxation into a semi-definite program. The last two approaches are showed to outperform the oracle multichannel Wiener filter in under-determined informed source separation tasks, using simulated and speech signals. The convex relaxation approach yields best results, including the potential for exact source separation in under-determined settings.

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