多通道非负矩阵分解matlab代码

以下是一个简单的使用MATLAB实现多通道非负矩阵分解（MNMF）的示例代码：

function [W, H] = multi_channel_nmf(X, num_channels, num_components, max_iter)
    % 初始化W和H矩阵
    W = rand(size(X, 1), num_components);
    H = rand(num_components, size(X, 2), num_channels);
    
    % 迭代更新W和H矩阵
    for iter = 1:max_iter
        % 更新W矩阵
        for c = 1:num_channels
            V = X(:, :, c) * H(:, :, c)';
            W = W .* (X(:, :, c) * H(:, :, c)') ./ (W * V);
        end
        
        % 更新H矩阵
        for c = 1:num_channels
            V = W' * X(:, :, c);
            H(:, :, c) = H(:, :, c) .* (W' * X(:, :, c)) ./ (W' * W * H(:, :, c));
        end
        
        % 计算误差
        reconstruction_error = compute_error(X, W, H);
        fprintf('Iteration %d: Reconstruction error = %f\n', iter, reconstruction_error);
    end
end

% 计算重构误差
function error = compute_error(X, W, H)
    reconstructed_X = zeros(size(X));
    num_channels = size(X, 3);
    for c = 1:num_channels
        reconstructed_X(:, :, c) = W * H(:, :, c);
    end
    error = norm(X - reconstructed_X, 'fro');
end

% 示例用法
num_samples = 100;  % 样本数量
num_features = 50;  % 特征数量
num_channels = 3;  % 通道数量
num_components = 10;  % 分量数量
max_iter = 100;  % 最大迭代次数

% 生成随机数据
X = rand(num_samples, num_features, num_channels);

% 调用多通道非负矩阵分解函数
[W, H] = multi_channel_nmf(X, num_channels, num_components, max_iter);

请注意，这只是一个简单的示例代码，实际应用中可能需要根据具体情况进行更多的参数调整和优化。希望对您有帮助！如有其他问题，请随时提问。