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[AI-NN-PR] lsyc DL : 0: 信道容量C的迭代算法函数说明： [CC,Paa]=ChannelCap(P,k) 为信道容量函数变量说明： P：输入的正向转移概率矩阵，k：迭代计算精度 CC：最佳信道容量，Paa：最佳输入概率矩阵 Pa：初始输入概率矩阵，Pba：正向转移概率矩阵 Pb：输出概率矩阵，Pab：反向转移概率矩阵 C：初始信道容量， r：输入符号数，s：输出符号数 -Channel capacity C of the iterative algorithm Function Description: [CC, Paa] = ChannelCap (P, k) for the channel capacity function variable declaration: P: Enter a positive transition probability matrix, k: Diego generation of precision CC: Best channel capacity, Paa: optimal input probability matrix Pa: initial input probability matrix, Pba: positive transition probability matrix Pb: output probability matrix, Pab: reverse transition probability Matrix C: the initial channel capacity, r: the number of input symbols, s: output symbol number
Date : 2026-01-22 Size : 6kb User : lijing
[AI-NN-PR] xxs DL : 0: 信道容量C的迭代算法函数说明： [CC,Paa]=ChannelCap(P,k) 为信道容量函数变量说明： P：输入的正向转移概率矩阵，k：迭代计算精度 CC：最佳信道容量，Paa：最佳输入概率矩阵 Pa：初始输入概率矩阵，Pba：正向转移概率矩阵 Pb：输出概率矩阵，Pab：反向转移概率矩阵 C：初始信道容量， r：输入符号数，s：输出符号数 -Channel capacity C of the iterative algorithm Function Description: [CC, Paa] = ChannelCap (P, k) for the channel capacity function variable declaration: P: Enter a positive transition probability matrix, k: Diego generation of precision CC: Best channel capacity, Paa: optimal input probability matrix Pa: initial input probability matrix, Pba: positive transition probability matrix Pb: output probability matrix, Pab: reverse transition probability Matrix C: the initial channel capacity, r: the number of input symbols, s: output symbol number
Date : 2026-01-22 Size : 3kb User : lijing