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Mr Nikolajs Skuratovs

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Citation Author(s):
Nikolajs Skuratovs, Michael Davies
Submitted by:
Nikolajs Skuratovs
Last updated:
15 May 2020 - 7:04pm
Document Type:
Presentation Slides
Document Year:
2020
Event:
Presenters Name:
Nikolajs Skuratovs
Paper Code:
SAM-P2.11

Abstract 

Abstract: 

In this paper we consider the problem of recovering a signal x of size N from noisy and compressed measurements y = A x + w of size M, where the measurement matrix A is right-orthogonally invariant (ROI). Vector Approximate Message Passing (VAMP) demonstrates great reconstruction results for even highly ill-conditioned matrices A in relatively few iterations. However, performing each iteration is challenging due to either computational or memory point of view. On the other hand, a recently proposed Conjugate Gradient (CG) Expectation Propagation (CG-EP) framework is able to sacrifice some performance for efficiency, but requires access to exact singular spectrum of A. In this work we develop a CG-VAMP algorithm that does not require such information, is feasible to implement and converges to the neighborhood of the original VAMP.

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ICASSP_presentation_v2_pdf.pdf

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