De-noise data by using multivariate wavelets in the path analysis with application

Abstract EN

In this research dealing with pollution in multivariate data used in the analysis path through the purification by an algorithm proposed based on multivariate wavelets (Daubechies, bior and rbio) and soft thresholding and estimate of level in a way (Minimax) and then compare them with the results path analysis before dealing with pollution through the practical application of analyzing the causes of a problem water pollution in the Kurdistan region, concluded research on the proposed algorithm is efficient compared with the classical method depending on the MATLAB language and program (SPSS) with (Amos).