说明：  * 本算法用最小二乘法依据指定的M个基函数及N个已知数据进行曲线拟和 * 输入: m--已知数据点的个数M * f--M维基函数向量 * n--已知数据点的个数N-1 * x--已知数据点第一坐标的N维列向量 * y--已知数据点第二坐标的N维列向量 * a--无用 * 输出: 函数返回值为曲线拟和的均方误差 * a为用基函数进行曲线拟和的系数, * 即a[0]f[0]+a[1]f[1]+...+a[M]f[M].
(* The algorithm using the least-squares method based on the designated function of M and N-known curve data to be imported and* : m-- the known number of data points M* f-- From M* n vector function-- known data points the number N-1* x-- known data points of the first N-dimensional coordinates listed Vector* y-- known data points of the second N-dimensional coordinates shown in a vector*-- useless* Output : function return value to the curve-fitting and the mean square error* for the use of a base function and the curve fitting coefficients,* is a f [0] [0] a [1] f [a] ... a [M] f [M].)