Convexly constrained linear inverse problems: iterative least-squares and regularization
نویسندگان
چکیده
| In this paper, we consider robust inversion of linear operators with convex constraints. We present an iteration that converges to the minimum norm least squares solution; a stopping rule is shown to regularize the constrained inversion. A constrained Laplace inversion is computed to illustrate the proposed algorithm.
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ورودعنوان ژورنال:
- IEEE Trans. Signal Processing
دوره 46 شماره
صفحات -
تاریخ انتشار 1998