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California State University, Sacramento Sacramento State

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Volumes/cube6/iceAlbedoGlobeHD/images/iceAlglobalSD0483.sgi # (, ## % * (# #(# #7, #*# #,( % %% /7, #% #%###%# (,**,/##11% #/311,*(/1 Nuit Blanche:03/01/2015 - 04/01/2015Mar 31, 2015 · We examine in a unified framework both the L1 regularization (often referred to as Lasso or Basis-Pursuit) and the Continuous Basis-Pursuit (C-BP) methods. The Lasso is the de-facto standard for the sparse regularization of inverse problems in imaging. It performs a nearest neighbor interpolation of the spikes locations on the sampling grid. Szkoła Podstawowa nr 1 w Gniewkowie[ . O sjv n =, ] e N N ~V ]i ~e` 0cԌ J i $[[ > d 9. x e Fq 8 ` ⱖ Q} g s TѮ& C z ܋ ,/ 2 NA8> 9 ߌ_ n 'x X t d[-5 @ E TfC q x& NX" Q + vJ1 ?4c V R Mx $ @S @ ~] v n[ 9 .e H&k |˴X d L) Il 2 \Ou* 3Β#ʳI c 6 9!w P Vqi +%E +3 v` b H"2H B 2 ` NI 88 o CKF x P U#1 X* Q ; I& Y卌 L Ey @"6 L ` Fy }f᭖dԭ`>yfͫyi c - % H t MVY! n p P I;AP:{ v G- v

UMSL Mathematics and Computer Science

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