* 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].