文献1的仿真程序 solves the linear least squares problem with nonnegative variables = using the newton s algorithm in [1]. [1] Portugal, Judice and Vicente, A comparison of block pivoting and ％ interior point algorithms

可用于求解超大规模线性方程组非负解的MATLAB函数-Given a tall full-rank matrix A, solves the nonnegative least squares problem: min ||Ax-b|| s.t. x>= 0 and returns the minimizer x. The argument err is the tolerance used in testing