{"title":"用于跟踪后续出现的广义帕里克矩阵","authors":"Szilárd Zsolt Fazekas, Xinhao Huang","doi":"arxiv-2407.04462","DOIUrl":null,"url":null,"abstract":"We introduce and study a generalized Parikh matrix mapping based on tracking\nthe occurrence counts of special types of subsequences. These matrices retain\nmore information about a word than the original Parikh matrix mapping while\npreserving the homomorphic property. We build the generalization by first\nintroducing the Parikh factor matrix mapping and extend it to the Parikh\nsequence matrix mapping. We establish an interesting connection between the\ngeneralized Parikh matrices and the original ones and use it to prove that\ncertain important minors of a Parikh sequence matrix have nonnegative\ndeterminant. Finally, we generalize the concept of subword histories and show\nthat each generalized subword history is equivalent to a linear one.","PeriodicalId":501124,"journal":{"name":"arXiv - CS - Formal Languages and Automata Theory","volume":"41 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Generalized Parikh Matrices For Tracking Subsequence Occurrences\",\"authors\":\"Szilárd Zsolt Fazekas, Xinhao Huang\",\"doi\":\"arxiv-2407.04462\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We introduce and study a generalized Parikh matrix mapping based on tracking\\nthe occurrence counts of special types of subsequences. These matrices retain\\nmore information about a word than the original Parikh matrix mapping while\\npreserving the homomorphic property. We build the generalization by first\\nintroducing the Parikh factor matrix mapping and extend it to the Parikh\\nsequence matrix mapping. We establish an interesting connection between the\\ngeneralized Parikh matrices and the original ones and use it to prove that\\ncertain important minors of a Parikh sequence matrix have nonnegative\\ndeterminant. Finally, we generalize the concept of subword histories and show\\nthat each generalized subword history is equivalent to a linear one.\",\"PeriodicalId\":501124,\"journal\":{\"name\":\"arXiv - CS - Formal Languages and Automata Theory\",\"volume\":\"41 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Formal Languages and Automata Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2407.04462\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Formal Languages and Automata Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.04462","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Generalized Parikh Matrices For Tracking Subsequence Occurrences
We introduce and study a generalized Parikh matrix mapping based on tracking
the occurrence counts of special types of subsequences. These matrices retain
more information about a word than the original Parikh matrix mapping while
preserving the homomorphic property. We build the generalization by first
introducing the Parikh factor matrix mapping and extend it to the Parikh
sequence matrix mapping. We establish an interesting connection between the
generalized Parikh matrices and the original ones and use it to prove that
certain important minors of a Parikh sequence matrix have nonnegative
determinant. Finally, we generalize the concept of subword histories and show
that each generalized subword history is equivalent to a linear one.