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Preliminary evaluation of Bollinger deadband filtering using upper and lower bands

Authors: Nunzio Marco Torrisi;

Preliminary evaluation of Bollinger deadband filtering using upper and lower bands

Abstract

In this paper, the author investigates the use of the Bollinger Bands™ theory to compute the deadband sampling algorithm of unbounded variables. In this scenario the dead-band algorithm has to be adapted to compute the Altering using a new dynamically preset interval derived from the Bollinger Bands theory for financial applications. The number of filtered samples and the integral absolute error are adopted as metrics to compare performance results of the new original deadband proposed, named Bollinger Deadband, with the results of the classic absolute deadband algorithm. The signals adopted for the simulation are based on the pseudo periodic time series. For these signals the effectiveness of the Bollinger deadband is explored as alternative sampling method when the signal limits are unknown a priori.

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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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
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