Time series trend dynamic segmentation method based on central point

The invention discloses a time sequence trend dynamic segmentation method based on a central point, and aims to establish an effective index for a time sequence database so as to better classify a time sequence. In the field of pattern classification, normal and abnormal conditions of electrocardiogram center hops are automatically distinguished, trend characteristics of a time sequence need to bequalitatively researched, and a time sequence trend segmentation result is dynamically determined on the basis that the overall trend and measurement errors of data are reserved. The method comprisesthe steps of firstly, obtaining effective central points according to a parameter change rule of a time sequence; according to a generation mode of a central point, obtaining dynamic segments of thetime sequence, and determining starting and ending positions and interval trend characteristics of the segments; and finally, establishing a trend segment index table according to the trend index connection of each segment of t