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The following code uses the hmm action in the hiddenMarkovModel action set to fit a Gaussian HMM to the cross-sectional time series data.

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Thus the control limits for the sigma chart are {0.11, 0.50} For Average Chart. Singular values plot of dynamic system - MATLAB sigma find out here now. A. Most processes are not control charted so R bar is not available B. The factor d2 works when the. Sigma Data Center is a powerful program used to evaluate statistics and training sessions. This training software enables you to quickly and easily configure your SIGMA device on a PC or Mac and to transmit and evaluate your trip data for a comprehensive, systematic analysis of your training progress. LCL = 3.5 – (0.89 * 0.3) = 3.23.

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EDIT: The topic I'm doing now is interferometry, and it produces fringes on each of the images. Each of these fringes will contain the phase values/information, what my code suppose to do is to retrieve the phase information/ values of each image and then I need to see the phase change/phase shift that happened on each image, but I'm not sure how I can do this and I fail to do so. Based on the algorithm, I need to prove that as the moisture level increase/decrease, the phase value will increase/decrease as well/ phase value will shift towards how may degree. Now I don't know am I suppose to see the phase change/phase shift of each image via a graph or other methods. I have attached an image to show the example of input images that I will be using. I hope I can get some help with this. Thank you.

Here is my code:

%This whole part is to generate a mesh plot, i still dont know what info %can get from here but just leave it first. x = linspace(-10,10,256); y = linspace(-10,10,256); [X,Y] = meshgrid(x,y); x0 = 0; % Center y0 = 0; % Center sigma = 2; % Beam Waistfringes A = 1; % Peak of the Beam %These 2 lines, res and Source, is basically input intensity. U need %this in order to get the exponential image to process ltr. res = ((X-x0).^2 + (Y-y0).^2)./(2*sigma^2); Source = A .* exp(-res); %These 2 lines is for mesh plot also, ignore first surf(Source); shading interp %Reading Fringe Image (Target) Target = imread('0ml(1).jpeg'); Target = rgb2gray(Target); Target = im2double(Target); %Get the size of Target [rowsimgA, colsimgA, numberOfColorChannelsimgA] = size(Source); [rowsimgB, colsimgB, numberOfColorChannelsimgB] = size(Target); %imresize function is basically to resize any image to a particular size. %In this code u can see that i resize the Source beam input to the same %size as the target image in the format of (Target, [rows, columns]) if rowsimgB ~= rowsimgA || colsimgA ~= colsimgB Target = imresize(Target, [rowsimgA colsimgA]); end %FFT process A = fftshift(ifft2(fftshift(Target))); %Initiate loop % The loop im not too sure yet, but basically when u multiplay the source % and the phase, u produce exponential image, and then u do fft and ifft in % order to reconstruct the image. for i = 1:Iterations B = abs(Source) .* exp(1i*angle(A)); C = fftshift(fft2(fftshift(B))); D = abs(Target) .* exp(1i*angle(C)); A = fftshift(ifft2(fftshift(D))); error = [error; (1/sqrt(rowsimgA*colsimgA)*sqrt(sum(sum(abs(C)-abs(Target)).^2)))]; end %Display Outputs figure(2), imagesc(Target), colorbar, title('Original Fringe') figure(3), i = 1:1:i; plot(i,(error')); title('Error'); %Phase Mask figure(4), imagesc(angle(A)), title('Phase Mask'); %Last Pattern figure(5), imagesc(abs(C)), colorbar, title('Reconstructed Image'); %Reconstructed Image (Phase Only) figure(6), imagesc(angle(D)), colorbar, title('Reconstructed Image (Phase Only)'); %Reconstructed Image (Amplitude Only) figure(7), imagesc(abs(D)), colorbar, title('Reconstructed Image (Amplitude Only)'); %Display Total Time Taken for Phase Retrieval toc;https://preview.redd.it/7xie47pnxxx51.png?width=659&format=png&auto=webp&s=26056a5b884ddfe2b98bdd6acf6b294ea77c2537

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