Patent ID: 7945570
Filing Date: 2011-05-17
Classification: G06K

Abstract:
1. A computer-implemented method for identifying local patterns in at least one time series data stream, the method comprising: generating multiple ordered levels of hierarchical approximation functions directly from at least one given time series data stream including at least one set of time series data, wherein the hierarchical approximation functions for each level of the multiple ordered levels is based upon wherein generating multiple ordered levels of hierarchical approximation functions includes generating multiple increasing consecutive numerically ordered levels, wherein the current window is a portion of the set of time series data divided into consecutive sub-sequences, and wherein the current window length along with the hierarchical approximating functions reduces an approximation error between the current window and the set of time series data portion, calculating the approximation error between the current window and the set of time series data portion; basing the current window length on the approximation error calculated between the current window and the set of time series data portion; wherein the time series data stream is divided into non-overlapping consecutive subsequences, wherein the current window length for the current window is larger than a current window length for a previous window in the multiple ordered levels of hierarchical approximation functions, wherein the hierarchical approximation functions for each of level of the multiple ordered levels is further based upon storing the multiple ordered levels of hierarchical approximation functions into memory after being generated.