Abstract
We have many kinds of data of time series such as stock prices. We understand time series with a natural language. We have proposed methods to express a global trend, local features and oscillation of time series in a natural language. When the data are similar to each other in the standard deviation and frequency of oscillation, our method can't express their oscillation well for some data. If the frequency of oscillation of data is low, we seem to understand oscillation with its state, the frequency, amplitude and phase of oscillation. If it is high, we seem to understand oscillation with the upper outline of the plotting, i.e., plotting of parts of local maximums of the data, and the lower outline of the plotting, i.e., plotting of parts of local minimums of the data. We propose a method for high frequency of oscillation to express the outline of the plotting with global trends and local features of local maximums and local minimums. We express the high frequency oscillation data with this method and verify its effectiveness.
