1.
The Application of Noise Independent Component Analysis in Multi-user Detection;
噪声独立分量分析在多用户检测中应用研究
2.
Noise Sources Recognition Based on Independent Component Analysis Technology
基于独立分量分析技术的内燃机噪声源识别
3.
Study on Diesel Combustion Noise Based on Independent Component Analysis and Time Frequency Analysis-Part I: Analysis of combustion noise
基于独立分量分析和时频分析的柴油机燃烧噪声研究Ⅰ:燃烧噪声分析
4.
The Method of Seismic Random Noise Blind Separation Based on ICA
基于独立分量分析的地震信号随机噪声盲分离方法应用研究
5.
Image denoising based on independent component analysis(ICA)
基于独立分量分析(ICA)的图像去噪方法
6.
Removal of noise and ECG artifact from EEG based on wavelet transform and independent component analysis
小波变换和独立分量分析去除脑电信号中的噪声和干扰
7.
Study on Signal De-noising Technology in Ultrasonic Testing Based on Independent Component Analysis Theory
基于独立分量分析理论的超声波检测信号降噪技术研究
8.
Study on Diesel Combustion Noise Based on Independent Component Analysis and Time Frequency Analysis-Part II: Effect of pilot injection
基于独立分量分析和时频分析的柴油机燃烧噪声研究Ⅱ:预喷射影响分析
9.
New algorithm of blind image separation in noisy mixtures based on independence component analysis
基于独立分量分析新算法的含噪图像盲分离
10.
Removing Artifacts and Extracting Patterns in EEG Based on ICA;
基于独立分量分析的脑电消噪与特征提取
11.
Study of Image Denoising Based on Independent Component Analysis
基于独立分量分析的图像去噪方法研究
12.
The Application of ICA in PET Image Denoising
独立分量分析在PET图像去噪处理中的应用
13.
Research on Earthquake Signal De-Noising Based on Independent Component Analysis
基于独立分量分析的地震信号去噪研究
14.
Electrocardiogram noise removal based on empirical mode decomposition and independent component analysis
基于经验模式分解与独立分量分析的心电信号消噪方法
15.
Independent Component Analysis and Its Applications of Image Feature Extraction and Denoising;
独立分量分析及其在图像特征提取和消噪中的应用
16.
Modified Fast Independent Component Analysis and Its Application on Noise Attenuation for Seismic Data
基于改进的快速独立分量分析方法的地震信号去噪研究
17.
Simulation experiment of extracting evoked potential based on the combination of independent component analysis and wavelet analysis
独立分量分析结合小波去噪算法提取诱发电位信号的仿真实验
18.
Application of Differentiating Defect Signals of Ultrasonic Testing Based on Independent Component Analysis Theory;
独立分量分析在超声波检测信号处理中的应用