Independent Component Analysis and Its Application to Signal Processing of Two-phase flow

被引：1
作者：
Li Qiangwei [1 ]
机构：
[1] Zhejiang Police Coll, Hangzhou 310053, Zhejiang, Peoples R China
来源：
PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 3 | 2008年
关键词：
Independent component analysis; Two-phase flow; Non-Gaussian characteristic; Noise;
D O I：
10.1109/CHICC.2008.4605173
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Since non-Gaussian characteristic of pressure signal of two-phase flow and Gaussian characteristic of noise match the nature of Independent Component Analysis (ICA), the new method based on ICA for noise processing of pressure signal of two-phase flow is presented. ICA is applied firstly to a simulation signal with high SNR and a simulation signal with low SNR. The simulation results show that ICA can separate useful information even in the presence of severe noise environments. Then ICA is applied to the pressure signal of gas-solid two-phase flow, and the pressure signal and the noise signal are separated successfully. The primary researches demonstrate the non-Gaussian characteristic of pressure signal of gas-solid two-phase flow and show the effectiveness of ICA method in the noise processing of pressure signal of two-phase flow.
引用
收藏
页码：248 / 251
页数：4
相关论文
共 9 条
[1]   Neural networks for blind-source separation of Stromboli explosion quakes. [J].
Acernese, F ;
Ciaramella, A ;
De Martino, S ;
De Rosa, R ;
Falanga, M ;
Tagliaferri, R .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2003, 14 (01) :167-175
[2]   Face recognition by independent component analysis [J].
Bartlett, MS ;
Movellan, JR ;
Sejnowski, TJ .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 2002, 13 (06) :1450-1464
[3]  
CHEN CH, 2004, GEOSC REM SENS S, P3911
[4]  
Hyvarinen A, 1998, ADV NEUR IN, V10, P273
[5]   Fast and robust fixed-point algorithms for independent component analysis [J].
Hyvärinen, A .
IEEE TRANSACTIONS ON NEURAL NETWORKS, 1999, 10 (03) :626-634
[6]   Independent component analysis:: algorithms and applications [J].
Hyvärinen, A ;
Oja, E .
NEURAL NETWORKS, 2000, 13 (4-5) :411-430
[7]   Temporally constrained ICA: An application to artifact rejection in electromagnetic brain signal analysis [J].
James, CJ ;
Gibson, OJ .
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2003, 50 (09) :1108-1116
[8]  
SUN T, 2002, INSTR MEAS TECHN C A, V2, P1471
[9]  
Yu X, 2004, IEEE SYS MAN CYBERN, P4804
1