Non-negative Independent Component Analysis Algorithm Based on 2D Givens Rotations and a Newton Optimization

被引：10

作者：

Ouedraogo, Wendyam Serge Boris ^{[1
,2
]}

Souloumiac, Antoine ^{[1
]}

Jutten, Christian ^{[3
]}

机构：

[1] CEA, LIST, Lab Outils Anal Donnees, F-91191 Gif Sur Yvette, France

[2] Natl Sch Engineers Tunis, Unite Signaux & Syst, Tunis 1002, Tunisia

[3] Univ Grenoble 1, UMR 5216 CNRS, GIPSA Lab, F-38402 Grenoble, France

来源：

LATENT VARIABLE ANALYSIS AND SIGNAL SEPARATION | 2010年 / 6365卷

关键词：

Non-negative ICA; Givens rotations; Newton optimization; Complexity calculation; SEPARATION;

D O I：

10.1007/978-3-642-15995-4_65

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, we consider the Independent Component Analysis problem when the hidden sources are non-negative (Non-negative ICA). This problem is formulated as a non-linear cost function optimization over the special orthogonal matrix group SO(n). Using Givens rotations and Newton optimization, we developed an effective axis pair rotation method for Non-negative ICA. The performance of the proposed method is compared to those designed by Plumbley and simulations on synthetic data show the efficiency of the proposed algorithm.

引用

页码：522 / +

页数：2

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