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chapter7c

于 2020-01-06 发布

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说明： He-Chen-Zhang多相流LBM模型《Multiphase Lattice Boltzmann Methods Theory and Application》书后代码(Multiphase Lattice Boltzmann Methods Theory and Application)

文件列表：

Chap7_2_Fortran\collision.for, 13467 , 2014-11-06
Chap7_2_Fortran\head.inc, 964 , 2014-11-06
Chap7_2_Fortran\main.for, 8884 , 2014-11-06
Chap7_2_Fortran\output.for, 898 , 2014-11-06
Chap7_2_Fortran\utility.for, 1851 , 2014-11-06
Chap7_1_Fortran\collision.for, 10134 , 2014-11-06
Chap7_1_Fortran\feq.for, 891 , 2014-11-06
Chap7_1_Fortran\head.inc, 927 , 2014-11-06
Chap7_1_Fortran\init.for, 3280 , 2014-11-06
Chap7_1_Fortran\IO.for, 4053 , 2014-11-06
Chap7_1_Fortran\main.for, 3722 , 2014-11-06
Chap7_1_Fortran\params.in, 269 , 2014-11-06

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下行信道加扰源码,matlab编写,方便对通信模型的仿真和学习(Downstream channel scrambling codes, matlab prepared to facilitate the simulation model for communication and learning)

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说明：隐马尔科夫模型是关于时序的概率模型，描述由一个隐藏的马尔科夫链随机生成不可观测的状态随机序列，再由各个状态生成一个观测而产生观测序列的过程。隐藏的马尔科夫链随机生成的状态的序列，称为状态序列；每个状态生成一个观测，而由此产生的观测的随机序列，称为观测序列。马尔科夫链由初始概率分布、状态转移概率分布以及观测概率分布确定(The hidden Markov model is a probabilistic model for time series. It describes the process of randomly generating unobservable state random sequences from a hidden Markov chain, and then generating an observation by each state to produce an observation sequence. A sequence of randomly generated states of hidden Markov chains, called a sequence of states; each state produces an observation, and the resulting random sequence of observations is called an observation sequence. Markov chain is determined by initial probability distribution, state transition probability distribution and observation probability distribution)

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