Posted by: nepaliraja September 9, 2009
Login in to Rate this Post:
0
?
Try least square. Here is a nonlinear solver
help lsqnonlin
LSQNONLIN solves non-linear least squares problems.
LSQNONLIN attempts to solve problems of the form:
min sum {FUN(X).^2} where X and the values returned by FUN can be
x vectors or matrices.
choose FUN = Y - X1 (a1 * V^{n1} + a2 * V^{n2} + a3 * V^{n3}) and put known constants Y, X1 and V. The x vectors would be [a1, a2, a3, n1, n2, n3]. It will find the least square i.e. FUN^2 for different possible of x. Minimum FUN^2 will be 0 so you will get Y = X1 (a1 * V^{n1} + a2 * V^ + {n2}a3 * V^{n3}) by changing a's and n's.
help lsqnonlin
LSQNONLIN solves non-linear least squares problems.
LSQNONLIN attempts to solve problems of the form:
min sum {FUN(X).^2} where X and the values returned by FUN can be
x vectors or matrices.
choose FUN = Y - X1 (a1 * V^{n1} + a2 * V^{n2} + a3 * V^{n3}) and put known constants Y, X1 and V. The x vectors would be [a1, a2, a3, n1, n2, n3]. It will find the least square i.e. FUN^2 for different possible of x. Minimum FUN^2 will be 0 so you will get Y = X1 (a1 * V^{n1} + a2 * V^ + {n2}a3 * V^{n3}) by changing a's and n's.