Nonlinear Alleviation of Edge Effects in the Context of Minimizing Prediction Errors

The aim of this article is to describe so-called “edge effects” in the context of wavelet analysis. The problem of “edge effects” is displayed in cases where the filter length is greater than 2. This is due to the fact that the calculation of the wavelet coefficients for the development of the last signal of finite elements, the filter - should theoretically move beyond the signal. The article describes different ways to solve this problem using an authored approach. One of the ways presented in the article is an innovative approach in terms of “edge effects”. The author’s proposal is based on the nonlinear function of the trend after the division of the series into smaller units. The results obtained show that in comparison with other methods, the author’s method reduces errors. In this article, the Daubechies wavelet was used for the study. The Daubechies wavelets are a family of orthogonal wavelets, characterized by a maximum number of vanishing moments for a given support.