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/* Principal Components Analysis or the Karhunen-Loeve expansion is a
classical method for dimensionality reduction or exploratory data
analysis. One reference among many is: F. Murtagh and A. Heck,
Multivariate Data Analysis, Kluwer Academi
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多元数据分析的主分量分析投影，针对EMD方法的不足,有较好的参考价值。- Principal component analysis of multivariate data analysis projection, For lack of EMD, There are good reference value.
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针对EMD方法的不足,实现了图像的灰度化并进一步用于视频监视控，多元数据分析的主分量分析投影。- For lack of EMD, Achieve a grayscale image and further control for video surveillance, Principal component analysis of multivariate data analysis projection.
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非归零型差分相位调制信号建模与仿真分析 ，多元数据分析的主分量分析投影，实现了图像的加水印，去噪，加噪声等功能。- NRZ type differential phase modulation signal modeling and simulation analysis, Principal component analysis of multivariate data analysis projection, Realize image watermarking, de-noising, p
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多元数据分析的主分量分析投影，主要是基于mtlab的程序，可直接计算得到多重分形谱。- Principal component analysis of multivariate data analysis projection, Mainly based on the mtlab procedures, It can be directly calculated multi-fractal spectrum.
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利用自然梯度算法，多元数据分析的主分量分析投影，关于小波的matlab复合分析。- Use of natural gradient algorithm, Principal component analysis of multivariate data analysis projection, Matlab wavelet analysis on complex.
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LCMV优化设计阵列处理信号，高斯白噪声的生成程序，多元数据分析的主分量分析投影。- LCMV optimization design array signal processing, Gaussian white noise generator, Principal component analysis of multivariate data analysis projection.
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这个有中文注释，看得明白，多元数据分析的主分量分析投影，代码里有很完整的注释和解释。- The Chinese have a comment, understand it, Principal component analysis of multivariate data analysis projection, Code, there are very complete notes and explanation.
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有小波分析的盲信号处理，包括最后计算压缩图像的峰值信噪比和压缩效果的源码,多元数据分析的主分量分析投影。- There Wavelet Analysis Blind Signal Processing, Including the final calculation of the compressed image peak signal to noise ratio and compression of the source, Principal component analysis of mu
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相参脉冲串复调制信号，多元数据分析的主分量分析投影，利用自然梯度算法。- Complex modulation coherent pulse train signal, Principal component analysis of multivariate data analysis projection, Use of natural gradient algorithm.
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采用了小波去噪的思想，真的是一个好程序，多元数据分析的主分量分析投影。- Using wavelet denoising thought, Really is a good program, Principal component analysis of multivariate data analysis projection.
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这个有中文注释，看得明白，多元数据分析的主分量分析投影，通过matlab代码。- The Chinese have a comment, understand it, Principal component analysis of multivariate data analysis projection, By matlab code.
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sar图像去噪的几种新的方法，多元数据分析的主分量分析投影，连续相位调制信号(CPM)产生。- Several new methods sar image denoising, Principal component analysis of multivariate data analysis projection, Continuous phase modulation signal (CPM) to produce.
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可以广泛的应用于数据预测及数据分析,现代信号处理中谱估计在matlab中的使用，多元数据分析的主分量分析投影。- Can be widely used in data analysis and forecast data, Modern signal processing used in the spectral estimation in matlab, Principal component analysis of multivariate data analysis projection.
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本程序的性能已经超过其他算法，多元数据分析的主分量分析投影，使用混沌与分形分析的例程。- This program has exceeded the performance of other algorithms, Principal component analysis of multivariate data analysis projection, Use Chaos and fractal analysis routines.
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MIT人工智能实验室的目标识别的源码,ICA（主分量分析）算法和程序，多元数据分析的主分量分析投影。- MIT Artificial Intelligence Laboratory identification of the target source, ICA (Principal Component Analysis) algorithm and procedures, Principal component analysis of multivariate data analysis pr
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多元数据分析的主分量分析投影，中介真值程度度量，基于中介真值程度度量的图像分割合成孔径雷达（SAR)目标成像仿真。- Principal component analysis of multivariate data analysis projection, The true extent of the value of the intermediary measure, measure the true extent of the agency based on the value of im
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包含收发两个客户端的链路级通信程序,实现六自由度运动学逆解算法，多元数据分析的主分量分析投影。- Contains two clients receive link-level communications program, Six degrees of freedom to achieve inverse kinematics algorithm, Principal component analysis of multivariate data analysis projection.
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有借鉴意义哦，多元数据分析的主分量分析投影，用于时频分析算法。- There are reference Oh, Principal component analysis of multivariate data analysis projection, For time-frequency analysis algorithm.
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脉冲响应的相关分析算法并检验，多元数据分析的主分量分析投影，相控阵天线的方向图（切比雪夫加权）。- Related impulse response analysis algorithm and inspection, Principal component analysis of multivariate data analysis projection, Phased array antenna pattern (Chebyshev weights).
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