Blind source separation using recursive TDD : Introduction of a threshold on separation performance
スポンサーリンク
概要
- 論文の詳細を見る
For most of the blind separation methods of convolutive mixtures, the parameters of unmixing filter are derived in frequency domain. This leads to a seldom mentioned hut important problem that generally the independence assumption between source signals collapses in frequency domain because of the inadequate samples. There exists correlation at each frequency bin. Sometimes it is too high to be neglected and consequently degrades the performance of all the BSS methods in various degrees. In this paper, we propose a recursive algorithm for lowering the unfavorable effect from the correlation, and combine it with the TDD-based blind separation method proposed by S. Ikeda and N. Murata. The bin mixtures are separated into the components of the sources as practical instead of the independent bins as achieved by the conventional method. The signal-to-noise ratio is greatly increased at certain bins, which results in a much better separation.
- 社団法人日本音響学会の論文
著者
-
Hu Xue
Graduate School Of Bio-applications And Systems Engineering Tokyo University Of Agriculture & Te
-
Kobatake H
Tokyo Univ. Agriculture & Technol. Tokyo Jpn
-
胡 学斌
東京農工大・BASE
-
Hu X
Graduate School Of Bio-applications And Systems Engineering Tokyo University Of Agriculture & Te
-
HU Xuebin
Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Tec
-
KOBATAKE Hidefumi
Graduate School of Bio-Applications and Systems Engineering, Tokyo University of Agriculture and Tec
-
Hu Xuebin
Tokyo University Of Agriculture And Technology
-
Hu Xuebin
Graduate School Of Bio-applications And Systems Engineering Tokyo University Of Agriculture And Tech
-
Kobatake Hidefumi
Graduate School Of Bio-applications And Systems Engineering Tokyo Univ. Of Agriculture & Technol
関連論文
- BLIND SOURCE SEPARATION USING ICA AND ABF
- Blind Separation of Convolutive Mixtures Using Recursive TDD
- 周波数領域BSSのための再帰的なアルゴリズム
- 周波数領域BSSのための再帰的なアルゴリズム
- ICA Mixture Analysis of Four-Phase Abdominal CT Images(Biological Engineering)
- Trials of Independent Component Analysis on Multi-phase Abdominal CT Images (関連学会との共催によるバイオメディカルイメージング連合フォーラム) -- (領域抽出及び関連技術)
- Blind source separation using recursive TDD : Introduction of a threshold on separation performance
- A New Method for Solving the Permutation Problem of Frequency-Domain Blind Source Separation(Engineering Acoustics)
- Eigen-structure based near-field wideband sources localization
- A-10-5 Near-field Energy Source Localization
- Proposal of Atlas-guided Eigen-organ Method for Location Detection of Multi-Organs in Three Dimensional Medical Images(Joint Session 2)
- A Method of Combing Multiple Experts for Face Detection from Cluttered Images
- A Method of Combing Multiple Experts for Face Detection from Cluttered Images
- A Method of Combing Multiple Experts for Face Detection from Cluttered Images
- A Modified Exoskeleton for 3D Shape Description and Recognition
- LI-7 Face detection based on gradient features and polynomial neural network
- A Modified Exoskeleton and Its Application to Object Representation and Recognition
- Face Detection Using Principal Component Analysis and Polynomial Neural Network
- Robust Face Detection Using a Modified Radial Basis Function Network
- Technological Trends of CAD System for Mammography