馬爾科夫過程介紹ppt課件(編輯修改稿)
2025-06-03 12:05 本頁面
【文章內(nèi)容簡(jiǎn)介】 matrices A and B, let Let C=AB, we can get ?????????????nnnnnnaaaaaaaaaA???????212222111211?????????????nnnnnnbbbbbbbbbB???????212222111211?????????????niiiiaaaa?21?? ?? ?? ????? ?? ?? ?????????????nkkjnkkjniiknknikjikninkkjikniijnjinjijinkkjikijbbababacbabababac11 11 11 1122111 v e r y f o r 1)()()( so?So the matrix C has the property 2: all columns add to 1. Obviously, it has the property 1: all entries ≥ 0. Then we have proved that C is a Markov matrix. At last we use induction and could easily prove the lemma. Markov matrix’ other important properties =1 is an eigenvalue. other eigenvalues, in absolute value, smaller than 1. |λ|1. The voting results of a congressional election are represented by a vector x in R3 If we record the oute of the election every two years by the above vector and the oute of one election depends only on the results of the preced
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