matlab优化的参数传递.docVIP

1. 初学者最爱用但是最不提倡的方法：全局变量法 适用于MATLAB7以及以前或者以后的版本 function withaddtionpara1 global b c b = 2; c = 3.5; x0 =0; options = optimset(Display, off); % Turn off Display y = fsolve(@poly, x0, options) function y = poly(x) % Compute the polynomial. global b c y = x^3 + b*x + c; 2. 直接传递法 适用于MATLAB7以及以前或者以后的版本 根据： X=FSOLVE(FUN,X0,OPTIONS,P1,P2,...) passes the problem-dependent parameters P1,P2,... directly to the function FUN: FUN(X,P1,P2,...). Pass an empty matrix for OPTIONS to use the default values. 如果 options不需要设置，则用空矩阵（[]）占位 function withaddtionpara2 b = 2; c = 3.5; x0 =0; options = optimset(Display, off); % Turn off Display y = fsolve(@poly, x0, options,b,c) function y = poly(x,b,c) % Compute the polynomial. y = x^3 + b*x + c; 3. 采用evalin以及assignin函数法 适用于MATLAB7以及以前或者以后的版本 function withaddtionpara3 b = 2; c = 3.5; x0 =0; assignin(base,b,b); assignin(base,c,c); options = optimset(Display, off); % Turn off Display y = fsolve(@poly, x0, options) function y = poly(x) % Compute the polynomial. b = evalin(base,b); c = evalin(base,c); y = x^3 + b*x + c; 4. 匿名函数法（Anonymous function） 适用于MATLAB7以及以后的版本 function withaddtionparas4 options = optimset(Display, off); % Turn off Display b =2; c = 3.5; x0 =0; y = fsolve(@(x)mypoly(x,b,c), x0, options) function y = mypoly(x,b,c) y = x^3 + b*x + c; 5. 嵌套函数法(nested function) 适用于MATLAB7以及以后的版本 function withaddtionpara5 b =2; c = 3.5; x0 =0; options = optimset(Display, off); % Turn off Display y = fsolve(@poly, x0, options) function y = poly(x) % Compute the polynomial. y = x^3 + b*x + c; end end 6. 采用文件传递(有些太笨拙了的办法) 适用于MATLAB7以及以前或者以后的版本 function withaddtionpara6 b = 2; c = 3.5; x0 =0; save paras b c options = optimset(Display, off); % Turn off Display y = fsolve(@poly, x0, options) function y = poly(x) % Compute the polynomial. load paras.mat y = x^3 + b*x + c;