电子学报2017，Vol.45Issue(1)：29-36,8.DOI:10.3969/j.issn.0372-2112.2017.01.005
一种利用结构特点实现复数域联合对角化解盲源分离新算法研究及应用
Research on a New Structural Traits Based Complex-Valued Space Joint Diagonalization Algorithm for Blind Source Separation and Its Applications
摘要
Abstract
Joint diagonalization (JD) is an efficient tool for blind source separation (BSS) problems.However,most existing JD algorithms could only be used for real-valued space BSS problems and set many constraints on target matrices.In order to solve the general complex-valued space BSS problems,a structural traits based joint diagonalization (STBJD) algorithm is proposed.The algorithm discards pre-whitening procedure,relaxes the positive-definiteness assumption on target matrices and can be used in complex-valued space,thus has more general utilizations.Matrix transformation was adapted to transform the complex-valued space target matrices being jointly diagonalized to real-valued space ones with distinct structural traits.Furthermore,the Least Square cost function for JD was established and solved by alternate least squares (ALS) iterative algorithm.The structural traits of concerned variables were fully exploited and technical utilized in the optimizing process.Finally,the mixing matrix could be estimated and the sources could be retrieved.Numerical simulations illustrated the better convergence performance of STBJD than that of the state-of-the-art algorithms such as FAJD and CVFFDIAG.Thus it could be applied to solve the BSS problems efficiently.关键词
盲源分离/联合对角化/STBJD算法/交替最小二乘迭代算法Key words
blind source separation (BSS)/joint diagonalization (JD)/STBJD algorithm/alternate least squares iterative algorithm分类
信息技术与安全科学引用本文复制引用
徐先峰,段晨东,刘来君,杨小军..一种利用结构特点实现复数域联合对角化解盲源分离新算法研究及应用[J].电子学报,2017,45(1):29-36,8.基金项目
国家自然科学基金(No.61201407,No.61473047) （No.61201407,No.61473047）
中国博士后科学基金面上资助(No.2013M542309) （No.2013M542309）
陕西省自然科学基础研究计划(No.2016JQ5103) （No.2016JQ5103）
长安大学中央高校基本科研业务费(No.0009-2014G1321038) （No.0009-2014G1321038）
