Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4626008 | Applied Mathematics and Computation | 2016 | 7 Pages |
Abstract
By means of the properties of structured matrices from the design of Hopfield neural networks, we establish the necessary and sufficient conditions for the solvability of the inverse eigenvalue problem AX=XΛAX=XΛ in structured matrix set SARJn. In the case where AX=XΛAX=XΛ is solvable in SARJn, we derive the generalized representation of the solutions. In addition, in corresponding solution set of the equation, we provide the explicit expression of the nearest matrix to a given matrix in the Frobenius norm.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Lei Zhu, Wei-wei Xu,