1) independent component analysis
独立成份分析
1.
Independent component analysis in extracting sub-signal of ECG;
独立成份分析提取心电信号子成份
2.
Research on Joint Detection for TD-SCDMA Based on Independent Component Analysis;
基于独立成份分析的TD-SCDMA联合检测技术研究
3.
Independent component analysis (ICA) has been used to investigate the same face images under variant light conditions and three combination coefficients are randomly selected to simulate the distribution of these images in ICA subspace.
应用独立成份分析(ICA)方法研究了不同照明条件下同一姿势人脸的图像,并用图像在ICA空间中任意三个独立成分的组合系数模拟得出:1)强度变化的同一幅人脸图像分布在一条直线上;2)照明方向变化下的同一姿势人脸的图像按一定规则集中分布。
2) ICA
独立成份分析
1.
In order to overcome the shortcoming of the traditional methods,independent component analysis(ICA) is used to analyse the factor that has influence on the trend of stocks and the returns of stocks.
为了克服传统的股票分析方法的缺点,将独立成份分析方法用于分析影响股票走势和收益的因素。
2.
Independent component analysis (ICA) or blind source separation is a modern signal processing technique to multivariate financial time series such as a portfolio of stocks.
独立成份分析是一门新兴的盲源分离技术,它在金融时间序列方面的应用才刚刚开始。
3.
Furthermore,the feature vectors fused by independent component analysis(ICA)with global and local features were given.
该方法首先对预处理后的人脸图像进行全局特征及局部分量的提取,分别采用离散余弦变换(DCT)提取包含图像大量信息的低频部分特征和奇异值分解(SVD)抽取图像的代数特征作为图像的全局特征,采用非负矩阵分解(NMF)提取图像的局部分量特征,然后将此两类特征以独立成份分析(ICA)进行融合,获取用于人脸识别的特征向量。
4) independent component
独立成份
1.
The algorithm first makes use of latent semantic indexing to re-duce the dimension and wipe off noise,and then it introduces independent component analysis to extract statistic inde-pendent and semantic features.
该算法首先采用潜在语义分析降低文本的维数并去除噪声,然后运用独立成份分析方法在潜在语义特征中提取出最能表达语义且相互统计独立的特征。
2.
The algorithm first makes use of latent semantic indexing to reduce the dimension and wipe off noise, and then it introduces independent component analysis to extract statistic independent and semantic featur.
本文提出的算法首先采用潜在语义分析降低文本的维数并去除噪声,然后运用独立成份分析方法在潜在语义特征中提取出最能表达语义且相互统计独立的特征。
5) independent component analysis (ICA)
独立成分分析
1.
A local regression method was proposed based on independent component analysis (ICA) .
建立了一种基于独立成分分析的局部建模新方法,该方法首先将独立成分分析(ICA)用于近红外光谱的特征提取,然后,根据所提取的独立成分选择校正集中与预测样本相邻近的样本构成校正子集,建立局部偏最小二乘(PLS)回归模型并对预测样本进行预测。
2.
To overcome the shortcoming of the conventional process monitoring methods assumption that the extracted features must be subject to multivariate normal distribution, a novel method based on independent component analysis (ICA) and principal component analysis (PCA) was presented for process performance monitoring by using a two-step procedure.
为克服传统过程监控方法需假设过程特征信号服从多元正态分布的缺陷,提出了一种新的基于独立成分分析(ICA)和主元分析(PCA)的过程监控方法,该方法由两步组成:第一步:利用独立成分分析方法从过程信息中提取非正态分布特征信号,然后用Parzen窗法估计其概率密度确定控制限进行过程监控;第二步:利用主元分析方法对剩余过程信息提取正态分布特征信号,采用Q和HotellingT2统计量对此正态特征信号进行过程监控。
3.
In this paper, we show the basic mathematic model and separated algorithms of blind source separation (BSS)/ independent component analysis (ICA) firstly, we discuss in more detail uniqueness issues about the nonlinear BSS/ICA problems.
本文主要阐述了非线性盲源分离(BSS)/独立成分分析(ICA)模型的基本数学原理、分离算法、算法性能及其应用。
6) independent component analysis(ICA)
独立成分分析
1.
A new model building method of near-infrared(NIR) spectra based on independent component analysis(ICA) and support vector regression(SVR) was proposed.
首先采用独立成分分析(ICA)提取近红外光谱数据矩阵的独立成分和相应的混合矩阵,然后用支持向量机回归(SVR)对混合矩阵和实测浓度矩阵进行建模,建立了独立成分分析-支持向量机回归(ICA SVR)的近红外分析建模方法。
2.
Independent component analysis(ICA) is a new method of signal statistical processing and widely used in many fields.
独立成分分析是一种新的信号处理统计方法,被广泛用于各个领域。
3.
This paper proposes a dimensionality reduction and compression method of hyperspectral images based on Independent Component Analysis(ICA) for hyperspectral image analysis.
该文提出了一种以高光谱图像分析为目标的基于独立成分分析的高光谱图像降维和压缩方法。
补充资料：成份股指数
参考条目
- 上证指数
- 深证指数
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条