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Mr Nikolajs Skuratovs


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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Nikolajs Skuratovs, Michael Davies
Submitted On:
15 May 2020 - 7:04pm
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Nikolajs Skuratovs
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[1] Nikolajs Skuratovs, Michael Davies, "Mr Nikolajs Skuratovs", IEEE SigPort, 2020. [Online]. Available: Accessed: Sep. 24, 2020.
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author = {Nikolajs Skuratovs; Michael Davies },
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T1 - Mr Nikolajs Skuratovs
AU - Nikolajs Skuratovs; Michael Davies
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Nikolajs Skuratovs, Michael Davies. (2020). Mr Nikolajs Skuratovs. IEEE SigPort.
Nikolajs Skuratovs, Michael Davies, 2020. Mr Nikolajs Skuratovs. Available at:
Nikolajs Skuratovs, Michael Davies. (2020). "Mr Nikolajs Skuratovs." Web.
1. Nikolajs Skuratovs, Michael Davies. Mr Nikolajs Skuratovs [Internet]. IEEE SigPort; 2020. Available from :