Compression and Reconstruction of Time Series Data Based on Vector Valued Continued Fraction
Tian Bai · Journal of Information and Computational Science · 2014
In this paper we introduce a novel method to compress time series data based on interpolation of vector valued continued fraction. Compared with straight segments method, our method has a better compression. In our method, multiple attributes of an object can also be computed together by means of vector. Our method first get a raw series of compression data points by using top-down method, then the raw series is divided into some segments by using continued fraction interpolation. Finally, a discriminant criterion will help us to delete some compression points on segments. In reconstructing, piecewise interpolation of vector valued continued fraction is used to recover original data.