nested for loop for 2d matrix cell

Question

ARN 2020-5-22

0
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https://ww2.mathworks.cn/matlabcentral/answers/530243-nested-for-loop-for-2d-matrix-cell

评论： ARN 2020-5-22

Hi,

I have a cell RDM {1x10} and every cell contains (512x1024) matrix. Now i have applied the following algorithm on one Matrix which i have to apply on all the matrix.

I get error on indexing every time. How can i implement that for all 10 matrices?

Tr = 10;
Td = 8;
Gr = 4;
Gd = 4;
% offset the threshold by SNR value in dB
offset = 1.4;
for i = Tr+Gr+1:(fft_size/2)-(Gr+Tr)
    for j = Td+Gd+1:fft_size-(Gd+Td)
        noise_level = zeros(1,1);
        for p = i-(Tr+Gr) : i+(Tr+Gr)
            for q = j-(Td+Gd) : j+(Td+Gd)
                if (abs(i-p) > Gr || abs(j-q) > Gd)
                    noise_level = noise_level + 10.^(RDM(p,q)/10);
                end
            end
        end
        
        threshold = 10*log10(noise_level/(2*(Td+Gd+1)*2*(Tr+Gr+1)-(Gr*Gd)-1));
        threshold = threshold + offset;
        CUT = RDM(i,j);
        
        if (CUT < threshold)
            RDM(i,j) = 0;
        else
            RDM(i,j) = 1;
        end
        
    end
end

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Answer 1

Abdolkarim Mohammadi 2020-5-22

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https://ww2.mathworks.cn/matlabcentral/answers/530243-nested-for-loop-for-2d-matrix-cell#answer_436148

编辑：Abdolkarim Mohammadi 2020-5-22

在 MATLAB Online 中打开

I think the problem lies here

CUT = RDM(i,j);
if (CUT < threshold{o})

You said that RDM is a cell matrix; so CUT is also a cell matrix because it has been assigned using parantheses, not curly braces. But threshold{o} is double because you used implicit casting using curly braces. If this is the problem, then you must use

CUT = RDM{i,j};

This makes CUT a double and the comparison in the following line becomes possible.

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ARN 2020-5-22

again not the answer i am looking for. I want to implement for all cells in a for loop.

ARN 2020-5-22

在 MATLAB Online 中打开

something like that:

for k = length(RDM)
RDM{k} = RDM{k}/max(max(RDM{k}));
for i = Tr+Gr+1:(fft_size/2)-(Gr+Tr)
    for j = Td+Gd+1:fft_size-(Gd+Td)
        
       %Create a vector to store noise_level for each iteration on training cells
        %noise_level = cell{zeros(1,1)};
        
        % Calculate noise SUM in the area around CUT
        for p = i-(Tr+Gr) : i+(Tr+Gr)
            for q = j-(Td+Gd) : j+(Td+Gd)
                if (abs(i-p) > Gr || abs(j-q) > Gd)
                    noise_level{k} = noise_level{k} + 10.^(RDM{k}(p,q)/10);
                end
            end
        end
        
        % Calculate threshould from noise average then add the offset
        threshold{k} = 10*log10(noise_level{k}/(2*(Td+Gd+1)*2*(Tr+Gr+1)-(Gr*Gd)-1));
        threshold{k} = threshold{k} + offset;
        CUT{k} = RDM{k}(i,j);
        
        if (CUT{k} < threshold{k})
            RDM{k}(i,j) = 0;
        else
            RDM{k}(i,j) = 1;
        end
        
    end
end
end