چكيده لاتين :
The Least Squares Support Vector Machines (LS-SYM) is an improvement on the Support Vector Machines (SVM). Combined the LS-SYM with the Multi-Resolution Analysis (MRA), an improved algorithmthe
Multi-resolution Least Squares Support Vector Machines (MLS-SYM) algorithm is proposed in this study. With better approximation ability, the proposed algorithm has the same theoretical framework as the MRA. At
a fixed scale the MLS-SVM is a classical LS-SVM. However, the MLS-SVM can gradually approximate the target function at different scales. In experiment, the MLS-SYM is used as nonlinear systemיs identification, with better identification accuracy achieved.
