Tradeoffs Between Convergence Speed and Reconstruction Accuracy in Inverse Problems

Solving inverse problems with iterative algorithms is popular, especially for large data. Due to time constraints, the number of possible iterations is usually limited, potentially affecting the achievable accuracy. Given an error one is willing to tolerate, an important question is whether it is po...

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Veröffentlicht in:	IEEE transactions on signal processing Jg. 66; H. 7; S. 1676 - 1690
Hauptverfasser:	Giryes, Raja, Eldar, Yonina C., Bronstein, Alex M., Sapiro, Guillermo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.04.2018
Schlagworte:	Acceleration approximate computing approximation methods Compressed sensing Convergence convergence of numerical methods gradient methods Iterative algorithms iterative methods neural networks Noise measurement optimization Signal processing algorithms Training
ISSN:	1053-587X, 1941-0476
Online-Zugang:	Volltext
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