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Multi-channel sparse blind deconvolution, or convolutional sparse coding, refers to the problem of learning an unknown filter by observing its circulant convolutions with multiple input signals that are sparse.
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Q. Qu, X. Li, and Z. Zhu, “A nonconvex approach for exact and efficient multichannel sparse blind deconvolution,” in Advances in Neural Information Processing Systems , 2019, pp. 4015–4026
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H.-W. Kuo, Y. Lau, Y. Zhang, and J. Wright, “Geometry and symmetry in short-and-sparse deconvolution,” in International Conference on Machine Learning , 2019, pp. 3570–3580
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