光电工程
光電工程
광전공정
OPTO-ELECTRONIC ENGINEERING
2009年
9期
104-109
,共6页
盲信号处理%独立分量分析%梯度下降算法%串行矩阵更新%等变自适应分离
盲信號處理%獨立分量分析%梯度下降算法%串行矩陣更新%等變自適應分離
맹신호처리%독립분량분석%제도하강산법%천행구진경신%등변자괄응분리
blind signal processing%independent component analysis%gradient descent algorithm%serial matrix updating%equivariant adaptive separation
为了设计更多有效的独立分量分析(ICA)算法,本文提出了ICA梯度下降算法(GDA)的一般框架,覆盖了许多目前流行的算法,如Infomax,MMI,MLE等等.该框架由一种新的基于Ⅱ类超加(减)性函数的参比函数理论导出,并采用推广的EASI形式作为更新规则来获得更好的性能.同时本丈也展示了一个基于二次熵函数的框架使用例子,并提出了其梯度的快速计算方法,最后仿真证明了它的有效性.实验结果表明,该框架非常实用,可作为开发更多有效ICA算法的有利工具.
為瞭設計更多有效的獨立分量分析(ICA)算法,本文提齣瞭ICA梯度下降算法(GDA)的一般框架,覆蓋瞭許多目前流行的算法,如Infomax,MMI,MLE等等.該框架由一種新的基于Ⅱ類超加(減)性函數的參比函數理論導齣,併採用推廣的EASI形式作為更新規則來穫得更好的性能.同時本丈也展示瞭一箇基于二次熵函數的框架使用例子,併提齣瞭其梯度的快速計算方法,最後倣真證明瞭它的有效性.實驗結果錶明,該框架非常實用,可作為開髮更多有效ICA算法的有利工具.
위료설계경다유효적독립분량분석(ICA)산법,본문제출료ICA제도하강산법(GDA)적일반광가,복개료허다목전류행적산법,여Infomax,MMI,MLE등등.해광가유일충신적기우Ⅱ류초가(감)성함수적삼비함수이론도출,병채용추엄적EASI형식작위경신규칙래획득경호적성능.동시본장야전시료일개기우이차적함수적광가사용례자,병제출료기제도적쾌속계산방법,최후방진증명료타적유효성.실험결과표명,해광가비상실용,가작위개발경다유효ICA산법적유리공구.
To design more effective algorithms for Independent Component Analysis (ICA), a general framework of Gradient Descent Algorithms (GDAs) for ICA was proposed, which covers many popular algorithms such as Infomax, Minimization of Mutual Information (MMI), Maximum Likelihood Estimation (MLE) and so on. This framework was derived from a new theory of the contrast functions for ICA based on the superadditive (or subadditive) function of class Ⅱ. For better performances, the Equivariant Adaptive Separation via Independence (EASI) form was generalized and used as the updating rule. An example of using the framework was also shown based on the quadratic entropy. Furthermore, a fast method of computing the gradient in the example was proposed and the simulation proved its validity. The results demonstrate that this framework is a useful tool to discover more effective algorithms for ICA.
