馬爾科夫過程介紹ppt課件-在線瀏覽
2025-06-24 12:05本頁面
【正文】 ilities that the oute of the experiment that is one of n possible outes. For this reason, xk is often called a state vector. So the population distribution could be Similarly, the distribution in 2022 is described by a vector x2, where What is Markov matrix? An nxn matrix whose form satisfies two properties below entries ≥0。 columns add to 1。s longterm behaver. For instance, what can be said in Example 2 about the voting after many elections have passed(assuming that the given stochastic matrix continues to describe the transition percentages from one election to the next)? Or, what happens to the population distribution in Example 1 in the long run? Before answering these questions, we turn to a numerical example. ??????????????????????001 and ...Let 0xPThe results of further calculations are shown below These vectors seem to be approaching q=[ ]T For the vector q, we can verify the below equation(with no rounding error) When the system is in state q, there is no change in the system from one measurement to the next. A vector q like this called a steadystate vector(or equilibrium vector)for
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