1) Independent Component Analysis with Reference(ICA-R)
参考独立成分分析
3) 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。
4) 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。
5) independent component analysis (ICA)
独立成分分析(ICA)
6) independent component analysis(ICA)
独立成分分析(ICA)
补充资料：参考
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