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The features of gene expression are extracted by the wavelet multi-resolution analysis, the features are classified by the support vector machines and BP neural network methods.
采用小波多分辩率分析方法提取基因表达的特征，利用支持向量机和BP神经网络方法进行分类。
For the problem of large amount of GIS map data, the algorithm of data compression by multi-resolution analysis and border processing is presented.
针对地理信息系统地图数据量大的问题，提出了多分辨分析数据压缩和边界处理方法。
After the wavelet's multi-resolution analysis, a feature fusion approach was adopted to enhance remote sensing image edge and improve the definition and resolving power of the image.
在数字图像小波多分辨率分析理论基础上，采用小波变换方法对高分辨遥感图像的目标地物边缘进行信息增强，然后与多光谱遥感图像进行特征信息融合。
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