… We present algorithms for compressing a time series by extracting its major extrema, that
is, minima and maxima. First, we define four types of extrema and describe an algorithm that …

… We formalise the notion of important extrema of a time series, that is, its major minima and …
of important extrema; and apply these results to the problem of time-series compression. First, …

… for comparing and analyzing time series is a fundamentally important problem. Research …
the extraction of interest points from time series. Recently, extrema features for analysis of …

… Motivated by the fundamental importance of extrema feature in diverse time series tasks (similarity
search, compression, indexation, etc.), our objective in this paper is to investigate its …

… Important minima and maxima are often called major extrema. Using major extrema of
time series, we can segment time series sensibly and visually into subsequences …

We describe techniques for fast compression of time series and hierarchical indexing of
compressed series based on the assignment of importance levels to the extrema of time series …

… to test whether the number of extrema for unit time of an experimental time series s(t) can be
… Another important point that we faced is whether the PSC and NET algorithms were able to …

… The identification and analysis of the extrema in a given time series is … extrema can provide
useful robust features [3], especially for robust learning [27]. The extrema are very important …

… Time series is an important form of data in various domains of industry and research, and the
interest in time series … The “importance” of extrema is defined by a threshold parameter R > …

… The task of extracting feature vectors from time series data is of fundamental importance in
accomplishing a wide range of pattern recognition tasks. A wide array of solutions have been …