Jan 17, 2017 · Abstract:In this work we characterize all ambiguities of the linear (aperiodic) one-dimensional convolution on two fixed finite-dimensional ...
Jan 17, 2017 · In the next section we will introduce an efficient recovery algorithm given by a convex program with the knowledge of additional autocorrelation ...
Bibliographic details on Blind Deconvolution with Additional Autocorrelations via Convex Programs.
We consider the problem of recovering two unknown vectors, w and x, of length L from their circular convolution. We make the structural assumption that the ...
Missing: Autocorrelations | Show results with:Autocorrelations
In this work we consider one-dimensional blind deconvolution with prior knowledge of signal autocorrelations in the classical framework of polynomial
Missing: via | Show results with:via
People also ask
What is blind deconvolution?
What is blind deconvolution in signal processing?
Abstract. We study the Short-and-Sparse (SaS) deconvolution problem of recovering a short signal a0 and a. 4 sparse signal x0 from their convolution.
Convex Blind Deconvolution with Random Masks | Request PDF
www.researchgate.net › publication › 26...
We solve blind deconvolution problems where one signal is modulated by multiple random masks using nuclear norm minimization. Theoretical analysis shows the ...
Abstract: We solve blind deconvolution problems where one signal is modulated by multiple random masks using nuclear norm minimization. Theoretical analysis ...
Missing: Additional | Show results with:Additional
Abstract—We introduce a novel multichannel blind de- convolution (BD) method that extracts sparse and front- loaded impulse responses from the channel ...
Jan 17, 2014 · A classical strategy for blind seismic deconvolution is to first estimate the autocorrelation of the unknown source wavelet from the data ...
Missing: Additional | Show results with:Additional