Finding zeroes of data for multiple trials

Question

LRW 2020-12-21

0
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/699665-finding-zeroes-of-data-for-multiple-trials

回答： Image Analyst 2020-12-21

I have found that the answer to another question on MATLAB Answers (found here: Previous Question) works for finding the zeroes of one of my data trials (see code below).

x = QF02num(:,1);
y = QF02num (:,2);
%%Code is from Star Strider in Previous Question (see link above)
zci = @(v) find(v(:).*circshift(v(:), [-1 0]) <= 0);                    % Returns Approximate Zero-Crossing Indices Of Argument Vector
dy = zci(y);                                                            % Indices of Approximate Zero-Crossings
for k1 = 1:size(dy,1)-1
    b = [[1;1] [x(dy(k1)); x(dy(k1)+1)]]\[y(dy(k1)); y(dy(k1)+1)];      % Linear Fit Near Zero-Crossings
    x0(k1) = -b(1)/b(2);                                                % Interpolate :Exact, Zero Crossing
    mb(:,k1) = b;                                                       % Store Parameter Estimates (Optional)
end

However, my data consists of multiple trials. I have a matrix called QF02num(91X81) that has 81 trials of data for which I am wanting to find the zeroes. The length of these trials (or the number of rows) and the number of times the data will cross the x axis both vary from trial to trial.

I have tried adding a for loop to iteratively go through each column or trial but I'm not sure how to store the zeroes (x0) for all the trials into one matrix. How do I make it so x0 stores the values of each iteration or column (i)?

for i=size(QF02num,2);
x = QF02num(:,1);
y = QF02num (:,i);
%%Code is from Star Strider in Previous Question (see link above)
zci = @(v) find(v(:).*circshift(v(:), [-1 0]) <= 0);                    % Returns Approximate Zero-Crossing Indices Of Argument Vector
dy = zci(y);                                                            % Indices of Approximate Zero-Crossings
for k1 = 1:size(dy,1)-1
    b = [[1;1] [x(dy(k1)); x(dy(k1)+1)]]\[y(dy(k1)); y(dy(k1)+1)];      % Linear Fit Near Zero-Crossings
    x0(k1) = -b(1)/b(2);                                                % Interpolate :Exact, Zero Crossing
    mb(:,k1) = b;                                                       % Store Parameter Estimates (Optional)
end
end