{"title":"多值逻辑函数优化的前沿算法","authors":"M. Abd-El-Barr, M. Abd-El-Barr","doi":"10.1109/ISMVL.1998.679450","DOIUrl":null,"url":null,"abstract":"A new algorithm, called the Frontiers algorithm, for optimizing the number of product terms required for the implementation of monotonic and permuted monotonic MVL functions is proposed. All experimental system restricted to the case of 2 variable 4-valued set of logic functions has been programmed using the C language and was interfaced to the HAMLET CAD tool to implement the proposed algorithm. The system was tested using 2231 randomly generated monotonic and permuted monotonic functions. The results obtained indicate that the frontiers-based algorithm compares favorably to existing heuristic minimization techniques with the added advantage that it requires less number of implicants to represent the target functions.","PeriodicalId":377860,"journal":{"name":"Proceedings. 1998 28th IEEE International Symposium on Multiple- Valued Logic (Cat. No.98CB36138)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Frontier algorithm for optimization of multiple-valued logic functions\",\"authors\":\"M. Abd-El-Barr, M. Abd-El-Barr\",\"doi\":\"10.1109/ISMVL.1998.679450\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A new algorithm, called the Frontiers algorithm, for optimizing the number of product terms required for the implementation of monotonic and permuted monotonic MVL functions is proposed. All experimental system restricted to the case of 2 variable 4-valued set of logic functions has been programmed using the C language and was interfaced to the HAMLET CAD tool to implement the proposed algorithm. The system was tested using 2231 randomly generated monotonic and permuted monotonic functions. The results obtained indicate that the frontiers-based algorithm compares favorably to existing heuristic minimization techniques with the added advantage that it requires less number of implicants to represent the target functions.\",\"PeriodicalId\":377860,\"journal\":{\"name\":\"Proceedings. 1998 28th IEEE International Symposium on Multiple- Valued Logic (Cat. No.98CB36138)\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-05-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings. 1998 28th IEEE International Symposium on Multiple- Valued Logic (Cat. No.98CB36138)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISMVL.1998.679450\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings. 1998 28th IEEE International Symposium on Multiple- Valued Logic (Cat. No.98CB36138)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISMVL.1998.679450","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Frontier algorithm for optimization of multiple-valued logic functions
A new algorithm, called the Frontiers algorithm, for optimizing the number of product terms required for the implementation of monotonic and permuted monotonic MVL functions is proposed. All experimental system restricted to the case of 2 variable 4-valued set of logic functions has been programmed using the C language and was interfaced to the HAMLET CAD tool to implement the proposed algorithm. The system was tested using 2231 randomly generated monotonic and permuted monotonic functions. The results obtained indicate that the frontiers-based algorithm compares favorably to existing heuristic minimization techniques with the added advantage that it requires less number of implicants to represent the target functions.