Gradient projection algorithm

Description

x = grad_proj(b, lambda, pars)

b is the constant term in the Frobenius norm.

lambda is the weight on the total variation penalty.

pars is a structure with additional parameters:

tol is the cutoff for the normed difference between successive iterates. 

If the difference falls below tol, the algorithm terminates.

max_iters is the maximum number of iterations.

bnds is a vector of the lower and upper bounds on the signal.

dom is a binary matrix that equals 1 for all pixels in the non-zero support set.

tv_type is the type of total variation penalty to use. Must be 'isotropic' or 'anisotropic'.


https://matlab1.com/stochastic-gradient-descent/
https://matlab1.com/gradient-descent/