Phase Difference Measurement Method for Sine Signals Based on Fast ICA

2013 Fourth Global Congress on Intelligent Systems Pub Date : 2013-12-03 DOI:10.1109/GCIS.2013.46

Gong Guoliang, Lu Huaxiang, Chen Gang, Jin Min, Chen Xu

引用次数: 5

Abstract

Noise is the key to cause phase measurement error of sine signals. Although there have been many attempts to suppress noise interference, high accuracy is still hard to meet in terrible noise environment. In order to improve reliability and accuracy of the measurement system, a robust method is proposed. In this paper, independent component analysis (ICA) is used to separate sine signal from noises. Firstly, an ICA model, which compensate the number of observed signals and its components is established. Then, the relationship of separation order of the independent components with measurement error is revealed, and a sorting algorithm based on priori knowledge is proposed to improve separation accuracy. Experimental results indicate the method is robust and accurate.

查看原文

微信好友朋友圈 QQ好友复制链接

本刊更多论文

基于快速ICA的正弦信号相位差测量方法

噪声是导致正弦信号相位测量误差的关键因素。虽然在抑制噪声干扰方面已经做了很多尝试，但是在恶劣的噪声环境下仍然很难达到高精度。为了提高测量系统的可靠性和精度，提出了一种鲁棒方法。本文采用独立分量分析(ICA)对正弦信号和噪声进行分离。首先，建立了ICA模型，对观测信号及其分量进行补偿;然后，揭示了独立分量的分离顺序与测量误差之间的关系，并提出了一种基于先验知识的排序算法来提高分离精度。实验结果表明，该方法具有较好的鲁棒性和准确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文去求助

来源期刊

2013 Fourth Global Congress on Intelligent Systems

自引率

0.00%

发文量

期刊最新文献

Using Bayesian Networks with Human Personality and Situation Information to Detect Emotion States from EEG Parameter Analysis of DDE-Based PID Controller Tuning Method Optimized Workforce Scheduling in Bus Transit Companies Reactions of Brain in English Reading Tests A Feature Representation Method of Social Graph for Malware Detection