清空筛选条件
清空筛选条件

Constraining a single element in non-negative least squares

1 次查看（过去 30 天）
Muhammad Haziq Kamarul Azman
Hello,
I'm using non-negative least squares to find a solution to a classic multi-parameter linear regression problem.
xhat = arg min J(x) = | | E x - f | |, subject to x >= 0,
with E a n-by-m matrix of rank m.
In one instance, I got what I needed using lsqnonneg. I then modify the problem as follows
xhat = arg min J(x) = | | Etilda x - ftilda | |, subject to x(m+1) >= 0 (i.e. only the last element of x is constrained),
with Etilda = [E etilda], etilda an n-vector. For the sake of simplicity, etilda is orthogonal to the column space of E (i.e. etilda is linearly independent of ej, the column vectors of E, j = [1:m]).
Is it possible to perform this optimization using lsqnonneg? If not, are there alternatives to that?

请先登录，再回答此问题。

回答（0 个）

类别

在 Help Center 和 File Exchange 中查找有关 Linear Least Squares 的更多信息

标签

产品

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by