Finite Markov chain imbedding and it's application to matching probability between two MAarkov

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  The length of the longest matching between two DNA sequences plays an im portant rule in genomic studies.The exact distribution of longest matching remains unknown especially when both sequences are Markov dependent.In this talk, Finite Markov Chain imbedding (FMCI) technique will be introduced.Using the FMCI technique, the exact distribution of the length of the longest matching between two Markov dependent sequences will be in terms of transition probability matrix of imbedded Markov chain.Numerical results are provided to illustrate the theoretical results.
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高尚全  1929年9月出生,上海嘉定人,汉族。教授小高级研究员。1952年毕业于土海圣约翰大学经济系,取得经济学学士学位。现任中国经济体制改革研究会会长,中国企业改革与发展研究会会长,中国经济改革研究基金会会长;第九届全国政协委员、经济委员会委员,联合国发展政策委员会委员;北京大学、上海交通大学兼职教授;博士生导师,浙江大学工商管理学院院长,澳大利亚国立大学NBA顾问,1993年享受国务院政府殊
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