ON INVERSE STOCHASTIC RECONSTRUCTION PROBLEM

Some results on the symmetric doubly stochastic inverse eigenvalue problem

‎The symmetric doubly stochastic inverse eigenvalue problem (hereafter SDIEP) is to determine the necessary and sufficient conditions for an $n$-tuple $sigma=(1,lambda_{2},lambda_{3},ldots,lambda_{n})in mathbb{R}^{n}$ with $|lambda_{i}|leq 1,~i=1,2,ldots,n$‎, ‎to be the spectrum of an $ntimes n$ symmetric doubly stochastic matrix $A$‎. ‎If there exists an $ntimes n$ symmetric doubly stochastic ...

On the seismic inverse problem: uniqueness, stability and reconstruction

Source Reconstruction as an Inverse Problem

Inverse Problem techniques offer powerful tools which deal naturally with marginal data and asymmetric or strongly smoothing kernels, in cases where parameter-fitting methods may be used only with some caution. Although they are typically subject to some bias, they can invert data without requiring one to assume a particular model for the source. The Backus-Gilbert method in particular concentr...

On the Inverse Problem of Constrained Data Reconstruction

Stochastic Inverse Minimum Spanning Tree Problem†

An inverse minimum spanning tree problem is to make the least modification on the edge weights such that a predetermined spanning tree is a minimum spanning tree with respect to the new edge weights. In this paper, the stochastic inverse minimum spanning tree problem is investigated. The concept of α-minimum spanning tree is initiated, and subsequently an α-minimum spanning tree model and a pro...