A method for detection of repetitive local effects (RLEs) in discrete recursive processes

Abstract

One-dimensional discrete processes, which can be measured repetitively for discrete values of arguments after discrete periodic or non periodic intervals of time, are discussed in this study. These processes can be under effect of different perturbations with different frequency, amplitudes, with accidental measurement error, etc. The problem investigated, is whether repetitive, local, relatively small effects (RLEs) can be extracted from this data. A simple method for such effects detection is proposed. A model for the simulation of discrete processes with local effects is introduced. Experiments with the method indicate that it is stable in detecting local effects and can be useful for many applications.

Keywords

• Discrete time series; Filtering; Patterns recognition.