{"title":"零混叠压缩","authors":"S. Gupta, D. Pradhan, S. Reddy","doi":"10.1109/FTCS.1990.89373","DOIUrl":null,"url":null,"abstract":"A compression technique, called periodic quotient compression, which eliminates the problem of aliasing is presented. The compression in signature analysis is based on polynomial division, where the remainder is the signature and the quotient is discarded. With this technique one looks at both the remainder and the quotient and assumes that the good circuit response is known a-priory during the design of the linear feedback shift register (LFSR). The concept of periodic polynomials is used to completely characterize the quotient, thus eliminating aliasing. The maximum number of bits required to compress an N-b response to achieve zero aliasing is determined. The authors provide an algorithm for constructing an LFSR to achieve this bound for any given circuit under test.<<ETX>>","PeriodicalId":174189,"journal":{"name":"[1990] Digest of Papers. Fault-Tolerant Computing: 20th International Symposium","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":"{\"title\":\"Zero aliasing compression\",\"authors\":\"S. Gupta, D. Pradhan, S. Reddy\",\"doi\":\"10.1109/FTCS.1990.89373\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A compression technique, called periodic quotient compression, which eliminates the problem of aliasing is presented. The compression in signature analysis is based on polynomial division, where the remainder is the signature and the quotient is discarded. With this technique one looks at both the remainder and the quotient and assumes that the good circuit response is known a-priory during the design of the linear feedback shift register (LFSR). The concept of periodic polynomials is used to completely characterize the quotient, thus eliminating aliasing. The maximum number of bits required to compress an N-b response to achieve zero aliasing is determined. The authors provide an algorithm for constructing an LFSR to achieve this bound for any given circuit under test.<<ETX>>\",\"PeriodicalId\":174189,\"journal\":{\"name\":\"[1990] Digest of Papers. Fault-Tolerant Computing: 20th International Symposium\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"21\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1990] Digest of Papers. Fault-Tolerant Computing: 20th International Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/FTCS.1990.89373\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1990] Digest of Papers. Fault-Tolerant Computing: 20th International Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FTCS.1990.89373","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A compression technique, called periodic quotient compression, which eliminates the problem of aliasing is presented. The compression in signature analysis is based on polynomial division, where the remainder is the signature and the quotient is discarded. With this technique one looks at both the remainder and the quotient and assumes that the good circuit response is known a-priory during the design of the linear feedback shift register (LFSR). The concept of periodic polynomials is used to completely characterize the quotient, thus eliminating aliasing. The maximum number of bits required to compress an N-b response to achieve zero aliasing is determined. The authors provide an algorithm for constructing an LFSR to achieve this bound for any given circuit under test.<>