
arXiv: 2201.12029
In 1999, S. V. Konyagin and V. N. Temlyakov introduced the so-called Thresholding Greedy Algorithm. Since then, there have been many interesting and useful characterizations of greedy-type bases in Banach spaces. In this article, we study and extend several characterizations of greedy and almost greedy bases in the literature. Along the way, we give various examples to complement our main results. Furthermore, we propose a new version of the so-called Weak Thresholding Greedy Algorithm (WTGA) and show that the convergence of this new algorithm is equivalent to the convergence of the WTGA.
Mathematics - Functional Analysis, Abstract approximation theory (approximation in normed linear spaces and other abstract spaces), almost greedy bases, Summability and bases; functional analytic aspects of frames in Banach and Hilbert spaces, FOS: Mathematics, greedy bases, thresholding greedy algorithm, Functional Analysis (math.FA)
Mathematics - Functional Analysis, Abstract approximation theory (approximation in normed linear spaces and other abstract spaces), almost greedy bases, Summability and bases; functional analytic aspects of frames in Banach and Hilbert spaces, FOS: Mathematics, greedy bases, thresholding greedy algorithm, Functional Analysis (math.FA)
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
