最小二乘法是系统辨识中最经典的方法，它通过最小化误差的平方和寻找数据的最佳函数匹配。利用最小二乘法可以简便地求得未知的数据，并使得这些求得的数据与实际数据之间误差的平方和为最小。最小二乘法还可用于曲线拟合。其他一些优化问题也可通过最小化能量或最大化熵用最小二乘法来表达。其中，RLS是递推最小二乘法程序，ELS是增广递推最小二乘法的程序。-

System identification least squares method is the most classic method, which matches the data by squaring and finding the best to minimize the error function. Least squares method can be easily calculated unknown data, and make the square error between the actual data and the data obtained and the minimum. Least squares method can be used for curve fitting. Some other optimization problems can be expressed using the method of least squares by minimizing energy or maximizing entropy. Wherein, RLS is a recursive least squares program, ELS is augmented recursive least squares method procedures.