稀疏矩阵到十进制编码(SMDC)算法

K. Afsal, Sainul Abideen, V. Kabeer
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引用次数: 0

摘要

我们最近引入了一种新的稀疏矩阵存储方法[1],该方法通过仅存储非零元素以及每行(或列)的权重和行(或列)的数量来大大减少存储空间。本文讨论了将稀疏矩阵转换为十进制编码格式的SMDC算法和将十进制编码的矩阵转换回标准稀疏矩阵格式的逆SMDC算法。SMDC是一种存储稀疏矩阵的空间优化存储方法。它可以存储一个m行n列、nnz个非零元素的稀疏矩阵,存储空间更小(m或n) + nnz +1,与大多数稀疏矩阵存储方法相比,是非常节省空间的存储方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sparse Matrix to Decimal Coding (SMDC) Algorithm
We recently introduced a new method for Sparse matrix storage[1] which will considerably reduce the storage space by storing only nonzero elements along with the weight of each row(or column) and the number of rows(or column). This paper discusses two algorithms, SMDC Algorithm to convert a sparse matrix into decimal coding format and Reverse SMDC Algorithm to convert a decimally coded matrix back into the normal sparse matrix format. SMDC is a space optimized storage method for storing sparse matrices. It can store a sparse matrix with m rows and n columns and nnz nonzero elements, with smaller (m or n) + nnz +1 storage space, which is very much space efficient storage compared to most of the sparse matrix storage methods.
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