An improvement on the basic Least Squares Support Vector Machine algorithm

The study on the least squares support vector machine (LS-SVM) algorithm is currently a dasiahotpsila area of support vector machine (SVM) study. Following Chua´s work and the algorithm analysis thought already used in system identification area, we make a further study to the basic LS-SVM, and make the algorithm more convenient to analyze the estimated parameters, as well as extend his thought to reduce the computing in the enlarged matrix dimension and new data adding cases. A view point is also shown in the paper, there are many similar analysis methods in system identification theory suit for LS-SVM analysis, and researchers can get twice the result with half the effort if utilize them intentionally when in study.