Effect Of Undersampling On Non-Negative Blind Deconvolution With Autoregressive Filters

This paper considers the problem of blind deconvolution where the input signal is non-negative and sparse, and the unknown convolutional kernel is a first order autoregressive filter. Our objective is to understand if it is possible to recover both the si
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