Performance Analysis of Signal Processing Based Periodicity Mining Tools

Abstract

Periodicity Mining is an area that deals with detection and identification of periodicities in any data. The work entails the analysis signal processing tools for periodicity mining and use it develop our proposed algorithm based on Intrinsic Integer-periodic function (IIPF).Our focus is to identify periodicities in a discrete integer periodic signals, whose periodic nature is far different than that of continuous time signals. The basis of the analysis is the idea that a signal or data has some hidden periodicity that are hard to estimate especially if the data is large. There are various signal processing tools for identifying periodicities in a given data or signal, like ML Techniques, CSMP Techniques, IIPF etc. We have developed Short-Time IIPF contrary to traditional IIPF. Thereafter, we have implemented and analysed the proposed algorithm on different DNA sequences