A new non-exact aho-corasick framework for ECG classification

Abstract

The Aho-Corasick (AC) algorithm is a popular and useful exact string matching algorithm for text searching and deep packet inspection. However, it has seldom been used for non-exact classification or identification. We propose a novel framework to make use of AC for non-exact matching in the ECG identification. The AC classification (ACC) algorithm converts ECG waveforms into several short patterns for AC, and decides the identification result by AC matched counting value. In our experiments, the results are surprisingly good and superior to previous algorithms. So, we designed an AC algorithm application for non-exact classification with high accuracy. Meanwhile, ACC inherits the advantage from AC of being capable of handling a large pattern set with linear time complexity.