A new approach for optimal offline time-series segmentation with error bound guarantee

Abstract

This paper proposes a new optimal approach, called OSFS, based on feasible space (FS) Liu et al. (2008)[, that minimizes the number of segments of the approximation and guarantees the error bound using the L∞-norm. On the other hand, a new performance measure combined with the OSFS method has been used to evaluate the performance of some suboptimal methods and that of the optimal method that minimizes the holistic approximation error (L2-norm). The results have shown that the OSFS method is optimal and demonstrates the advantages of L∞-norm over L2-norm.