STABLE AND FAST UPDATE RULES FOR INDEPENDENT VECTOR ANALYSIS BASED ON AUXILIARY FUNCTION TECHNIQUE

被引：0

作者：

Ono, Nobutaka ^{[1
]}

机构：

[1] Res Org Informat & Syst, Natl Inst Informat, Chiyoda Ku, Tokyo 1018430, Japan

来源：

2011 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA) | 2011年

关键词：

independent vector analysis; blind source separation; natural gradient; auxiliary function; SEPARATION;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper presents stable and fast update rules for independent vector analysis (IVA) based on auxiliary function technique. The algorithm consists of two alternative updates: 1) weighted covariance matrix updates and 2) demixing matrix updates, which include no tuning parameters such as step size. The monotonic decrease of the objective function at each update is guaranteed. The experimental evaluation shows that the derived update rules yield faster convergence and better results than natural gradient updates.

引用

页码：189 / 192

页数：4

共 45 条

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