1737f463aSAlp Dener /* 2*6e9726d0SXiang Huang Context for Bounded Regularized Gauss-Newton algorithm. 3*6e9726d0SXiang Huang Extended with L1-regularizer with a linear transformation matrix D: 4*6e9726d0SXiang Huang 0.5*||Ax-b||^2 + lambda*||D*x||_1 5*6e9726d0SXiang 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 11737f463aSAlp Dener #include <../src/tao/bound/impls/bnk/bnk.h> 12737f463aSAlp Dener 13737f463aSAlp Dener typedef struct { 14*6e9726d0SXiang Huang Mat J, H, D; /* Jacobian, Hessian, and Dictionary matrix have size M*N, N*N, and P*N respectively. */ 15*6e9726d0SXiang 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 P respectively. */ 16e1e80dc8SAlp Dener Tao subsolver, parent; 178ac80d48SXiang 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)*/ 18737f463aSAlp Dener } TAO_BRGN; 19737f463aSAlp Dener 20737f463aSAlp Dener #endif /* if !defined(__TAO_BRGN_H) */ 21