Stochastic Process

先放一个现成的CMakeLists.txt模板## 只需修改前三行set(_PROJECT_NAME_ "my_cuda_program") # project nameset(_EXE_NAME_ "sccu") # target nameset(_SRC_FILE_NAME_ "src") # source file locationcmake_minimum_required(VERSION 3.15)project(${_PROJECT_NAME_})## for cuda:# project(${_PROJECT_NAME_} LANGUAGES CXX CUDA)# find_package(CUDAToolkit REQUIRED)set(CMAKE_CXX_STANDARD 17)set(CMAKE_CXX_STANDARD_REQUIRED ON)# set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -Werr ...

离散时间马尔可夫链 (Markov Chain)一般来讲，为了化简一些过程，需要对对象进行一些假设，使其简单（无记忆性）、被大量随机过程满足、应用广泛。一个较好的假设，是现在的结果只依赖于最近一次的结果。 定义：设具有可数样本空间E的随机序列 ${X_m}_{m=0}^\infty$ 满足： $\forall k, \forall m_1<\cdots <m_{k+1},$ $\mathbb{P}(X_{m_{k+1}}=n_{k+1}|X_{m_{k+1}}=n_{k+1},\cdots ,X_{m_1}=n_1)=\mathbb{P}(X_{m_{k+1}}=n_{k+1}|X_{m_{k+1}}=n_{k+1})$; 则称 ${X_m}_{m=0}^\infty$ 为离散时间Markov链。化简条件后： $\forall k,\ \ \mathbb{P}(X_{m_{k+1}}=n_{k+1}|X_{m_{k+1}}=n_{k+1},\cdots ,X_{m_1}&#x ...