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Castro do Amaral, G. (author), Calliari, Felipe (author), Lunglmayr, Michael (author)
Trend break detection is a fundamental problem that materializes in many areas of applied science, where being able to identify correctly, and in a timely manner, trend breaks in a noisy signal plays a central role in the success of the application. The linearized Bregman iterations algorithm is one of the methodologies that can solve such a...
journal article 2020
document
Calliari, Felipe (author), Castro do Amaral, G. (author), Lunglmayr, Michael (author)
Detection of level shifts in a noisy signal, or trend break detection, is a problem that appears in several research fields, from biophysics to optics and economics. Although many algorithms have been developed to deal with such a problem, accurate and low-complexity trend break detection is still an active topic of research. The Linearized...
journal article 2020