馬爾科夫過程介紹ppt課件(已修改)
2025-05-19 12:05 本頁面
【正文】 APPLICATIONS TO MARKOV CHAINS 1211101 1121100210 應(yīng)用物理系 王允磊 What is Markov chains? The Markov chains described in this section are used as mathematical models of a wide variety of situations in biology, business, chemistry, engneering, physics, and elsewhere. In each case, the model is used to describe an experiment or measurement that is performed many times in the same way, where the oute of each trial of the experiment will be one of several specified possible outes, and where the oute of one trial depends only on the immediately preceding trial. For example, if the population of a city and its suburbs were measured each year, then a vector such as ???????0xcould indicate that 60% of the population lives in the city and 40% in the suburbs. The decimals in x0 add up to 1 because they account for the entire population of the region. Percentages are more convenient for our purpose here then population totals. A vector with nonnegative entries that add up to 1 is called a probability vector. A stochastic matrix is a square matrix whose columns are probability vectors. A Markov chain is a sequence of probability vectors x0, x1, x2
教學(xué)課件相關(guān)推薦
鄂ICP備17016276號-1