Semi-definite programming techniques for structured quadratic inverse eigenvalue problems

Matthew M. Lin, Bo Dong, Moody T. Chu

Research output: Contribution to journalArticlepeer-review

20 Citations (Scopus)


In the past decade or so, semi-definite programming (SDP) has emerged as a powerful tool capable of handling a remarkably wide range of problems. This article describes an innovative application of SDP techniques to quadratic inverse eigenvalue problems (QIEPs). The notion of QIEPs is of fundamental importance because its ultimate goal of constructing or updating a vibration system from some observed or desirable dynamical behaviors while respecting some inherent feasibility constraints well suits many engineering applications. Thus far, however, QIEPs have remained challenging both theoretically and computationally due to the great variations of structural constraints that must be addressed. Of notable interest and significance are the uniformity and the simplicity in the SDP formulation that solves effectively many otherwise very difficult QIEPs.

Original languageEnglish
Pages (from-to)419-437
Number of pages19
JournalNumerical Algorithms
Issue number4
Publication statusPublished - 2010 Apr

All Science Journal Classification (ASJC) codes

  • Applied Mathematics

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