1737f463aSAlp Dener /* 26e9726d0SXiang Huang Context for Bounded Regularized Gauss-Newton algorithm. 36e9726d0SXiang Huang Extended with L1-regularizer with a linear transformation matrix D: 46e9726d0SXiang Huang 0.5*||Ax-b||^2 + lambda*||D*x||_1 56e9726d0SXiang Huang When D is an identity matrix, we have the classic lasso, aka basis pursuit denoising in compressive sensing problem. 6737f463aSAlp Dener */ 7737f463aSAlp Dener 8737f463aSAlp Dener #if !defined(__TAO_BRGN_H) 9737f463aSAlp Dener #define __TAO_BRGN_H 10737f463aSAlp Dener 118e85b1b3SXiang Huang #include <../src/tao/bound/impls/bnk/bnk.h> /* BNLS, a sub-type of BNK, is used in brgn solver */ 12737f463aSAlp Dener 13737f463aSAlp Dener typedef struct { 14a3c390cfSAlp Dener PetscErrorCode (*regularizerobjandgrad)(Tao,Vec,PetscReal*,Vec,void*); 15a3c390cfSAlp Dener PetscErrorCode (*regularizerhessian)(Tao,Vec,Mat,void*); 16a3c390cfSAlp Dener void* reg_obj_ctx; 17a3c390cfSAlp Dener void* reg_hess_ctx; 18*30eeff36SXiang Huang Mat H,Hreg,D; /* Hessian, Hessian for regulization part, and Dictionary matrix have size N*N, and K*N respectively. (Jacobian M*N not used here) */ 198e85b1b3SXiang Huang Vec x_old,x_work,r_work,diag,y,y_work; /* x, r=J*x, and y=D*x have size N, M, and K respectively. */ 20e1e80dc8SAlp Dener Tao subsolver,parent; 218ac80d48SXiang Huang PetscReal lambda,epsilon; /* lambda is regularizer weight for both L2-norm Gaussian-Newton and L1-norm, ||x||_1 is approximated with sum(sqrt(x.^2+epsilon^2)-epsilon)*/ 22a3c390cfSAlp Dener PetscInt reg_type; 23737f463aSAlp Dener } TAO_BRGN; 24737f463aSAlp Dener 25737f463aSAlp Dener #endif /* if !defined(__TAO_BRGN_H) */ 26