#技术风云榜#分享列向量互信息计算通用MATLAB代码

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3 X9 M1 @) a/ x% g7 s* r通用MATLAB代码
, I$ o  R# a' H: N% g% ?5 @/ }主函数main.m

• clc
• u1 = rand(4,1);
• u2 = [2;32;6666;5];
• wind_size = size(u1,1);
• mi = calmi(u1, u2, wind_size);
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: K) B" v* ]- ?, I2 r5 [calmi.m
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• %计算两列向量之间的互信息
• %u1：输入计算的向量1
• %u2：输入计算的向量2
• %wind_size：向量的长度
• function mi = calmi(u1, u2, wind_size)
• x = [u1, u2];
• n = wind_size;
• [xrow, xcol] = size(x);
• bin = zeros(xrow,xcol);
• pmf = zeros(n, 2);
• for i = 1:2
•     minx = min(x(:,i));
•     maxx = max(x(:,i));
•     binwidth = (maxx - minx) / n;
•     edges = minx + binwidth*(0:n);
•     histcEdges = [-Inf edges(2:end-1) Inf];
•     [occur,bin(:,i)] = histc(x(:,i),histcEdges,1); %通过直方图方式计算单个向量的直方图分布
•     pmf(:,i) = occur(1:n)./xrow;
• end
• %计算u1和u2的联合概率密度
• jointOccur = accumarray(bin,1,[n,n]);  %（xi，yi）两个数据同时落入n*n等分方格中的数量即为联合概率密度
• jointPmf = jointOccur./xrow;
• Hx = -(pmf(:,1))'*log2(pmf(:,1)+eps);
• Hy = -(pmf(:,2))'*log2(pmf(:,2)+eps);
• Hxy = -(jointPmf(：）)'*log2(jointPmf(：）+eps);
• MI = Hx+Hy-Hxy;
• mi = MI/sqrt(Hx*Hy);
  

     

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列向量互信息计算通用MATLAB代码