样本熵matlab实现

样本熵的MATLAB实现可以使用以下代码：

function H = SampleEntropy(N, m, r, input)
for i = 1 : length(input)
    for j = 1 : N-m+1
        temp = input(i, j:j+m-1);
        A = [];
        for k = 1 : N-m+1
            if k ~= i
                dist = max(abs(temp-input(k, j:j+m-1)));
                if dist <= r
                    A = [A; k];
                end
            end
        end
        C(i, j) = length(A);
    end
end
B = sum(C);
H = -sum(B .* log(B/size(C, 2))) / size(C, 2);
end

这段代码实现了计算样本熵的函数。其中，N表示样本数据序列的长度，m表示采样熵的模板长度，r表示匹配窗口的差异阈值，input为输入的样本数据序列。在函数中，首先遍历每个样本，然后遍历每个子序列，计算其与其他子序列的距离，并根据阈值判断是否为匹配点。最后，统计每个窗口内的匹配点数，计算概率并计算样本熵。需要注意的是，若概率为0或1，需要取特殊值进行计算。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
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