项目作者: joe-lynch
项目描述 :
Numerical optimisation methods including the cauchy point, dogleg point, line search and steepest descent.
高级语言: MATLAB
项目地址: git://github.com/joe-lynch/numerical-optimisation.git
File Descriptions
dogleg.m
To run this function call dogleg(xn, fx, gx, H, H_, delta)\
[although is called as part of tr_dogleg]
where
- xn : initial point
- fx : actual function
- gx : gradient function
- H : Hessian matrix
- H_ : inverse Hessian matrix
- delta : radius of the trust region
sr1.m
To run this function call sr1(H, H_, d, y, eta)\
[although is called as part of tr_dogleg]
where
- H : Hessian matrix
- H_ : inverse Hessian matrix
- d : step between two points
- y : difference between gradient values
- eta : small value greater than zero
tr_dogleg.m
To run this function call trdogleg(f, df, H, H, xn, delta, delmax, rho_ac, tol)
where
- f : actual function
- df : gradient function
- H : Hessian matrix
- H_ : inverse Hessian matrix
- xn : initial point
- delta : radius of the trust region
- delmax : maximum radius of the trust region
- rho_ac : accuracy
- tol : tolerance
Note that eta, is defined as 10^(-6) in the file tr_dogleg.m