Semidefinite relaxation of quadratic optimization problems
Refereed conference paper presented and published in conference proceedings


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摘要In recent years, the semidefinite relaxation (SDR) technique has been at the center of some of very exciting developments in the area of signal processing and communications, and it has shown great significance and relevance on a variety of applications. Roughly speaking, SDR is a powerful, computationally efficient approximation technique for a host of very difficult optimization problems. In particular, it can be applied to many nonconvex quadratically constrained quadratic programs (QCQPs) in an almost mechanical fashion, including the following problem: © 2010 IEEE.
著者Luo Z.-Q., Ma W.-K., So A., Ye Y., Zhang S.
出版年份2010
月份5
日期1
卷號27
期次3
出版社Institute of Electrical and Electronics Engineers
出版地United States
頁次20 - 34
國際標準期刊號1053-5888
語言英式英語

上次更新時間 2021-02-03 於 03:18