Abstract:
There are many techniques developed for tackling time se-
ries and most of them consider every part of a sequence equally. In many
applications, however, recent data can often be much more interesting
and significant than old data. This paper defines new recent-biased measures for distance and energy, and proposes a recent-biased technique
based on DWT for time series in which more recent data are considered
more significant. With such a recent-biased technique, the dimension of
time series can be reduced while effectively preserving the recent-biased
energy. Our experiments have demonstrated the effectiveness of the pro-
posed approach for handling time series.
