条件概率矩阵和信道理论及Markov链

On conditioned probability matrix and channel theory and Marcov chains

给出离散型随机变量的概率分布律所成的单位空间的定义 ,将条件概率矩阵看作单位空间之间的映射 ,研究其中一些性质。并应用于信息论 ,得出信道容量的几何意义 ,特别给出信道容量的一种较好算法。应用于Markov链 ,得到状态有限的转移概率矩阵必有不动点。参

Regarding all dispersed stochastic variables distribution as “unit space” and treating conditioned probability matrixes as a mapping between unit spaces,the author applies these to information theory and obtains a better algorithm of channel capacity,and proves that there must be a steady point if the state of transition probability matrix in Marcov Chains is limited.