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广义延拓矩阵的奇异值分解

SINGULAR VALUE DECOMPOSITION FOR GENERALIZED EXTENDED MATRIX
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摘要 具有广义行或列对称性结构的矩阵(即广义延拓矩阵)的奇异值和奇异向量与原矩阵(母矩阵)的奇异值和奇异向量存在定量关系,从而对于广义延拓矩阵的奇异值分解,可利用母矩阵奇异值分解来实现。这不但可以节省计算量和运算量,而且不影响任何数据的精度。 The quantitative correspondence of the singular values and singular vectors between the generalized row or column symmetric matrix ( namely, generalized extended matrix) and its original (a. k. a mother matrix) were derived. The singular value decomposition of generalized extended matrix could save dramatically the memory by using the mother matrix and alleviate considerably the computation burden without loss of any numerical precision.
机构地区 九江学院理学院
出处 《九江学院学报》 2008年第6期1-3,共3页 JOurnal of Jiujiang University :Social Science Edition
基金 国家自然科学基金项目(60863012) 江西省自然科学基金项目(2007GZS1760) 江西省教育厅科技项目(重点GJJ08432)资助
关键词 奇异值分解 广义延拓矩阵 母矩阵 singular value decomposition generalized extended matrix mother matrix
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