The inverse eigenvalue problem of structured matrices from the design of Hopfield neural networks

Lei Zhu,Wei-Wei Xu

doi:10.1016/j.amc.2015.08.089

The inverse eigenvalue problem of structured matrices from the design of Hopfield neural networks

Lei Zhu, Wei-Wei Xu

https://doi.org/10.1016/j.amc.2015.08.089

Copy DOI

Journal: Applied Mathematics and Computation	Publication Date: Nov 12, 2015
Citations: 3

Affiliation: Nanjing Agricultural University, Nanjing University of Information Science and Technology

#Inverse Eigenvalue Problem #Design Of Neural Networks + Show 8 more

Abstract
Full-Text PDF
Similar Papers

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=XΛ in structured matrix set SARJn. In the case where AX=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.

Full Text