{"title":"稀疏矩阵到十进制编码(SMDC)算法","authors":"K. Afsal, Sainul Abideen, V. Kabeer","doi":"10.9790/9622-0707089294","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":13972,"journal":{"name":"International Journal of Engineering Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sparse Matrix to Decimal Coding (SMDC) Algorithm\",\"authors\":\"K. Afsal, Sainul Abideen, V. Kabeer\",\"doi\":\"10.9790/9622-0707089294\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":13972,\"journal\":{\"name\":\"International Journal of Engineering Research and Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Engineering Research and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9790/9622-0707089294\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Engineering Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9790/9622-0707089294","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.