perform global analysis on fluoresence decay curves. in matlab

To perform global analysis on fluorescence decay curves in MATLAB, you can use the following steps:

1. Load the fluorescence decay curve data into MATLAB. You can either import the data from a file or generate it programmatically.

2. Convert the time-domain fluorescence decay curves into the frequency-domain using a Fourier transform. This can be done using the fft function in MATLAB.

3. Choose an appropriate model for fitting the frequency-domain fluorescence decay curves. Common models include exponential decay models or stretched exponential models.

4. Define the objective function that represents the difference between the measured and fitted decay curves. This function should take the model parameters as input and return the residuals.

5. Use a fitting algorithm, such as the Levenberg-Marquardt algorithm implemented in the lsqcurvefit function in MATLAB, to minimize the objective function and obtain the optimal model parameters.

6. Perform the fitting for multiple fluorescence decay curves simultaneously, which is the essence of global analysis. This involves concatenating the frequency-domain decay curves and the objective function residuals for all curves.

7. Run the fitting algorithm on the concatenated data to obtain the global optimal model parameters for all decay curves.

8. Analyze the fitted parameters to extract meaningful information about the decay dynamics, such as lifetimes, amplitudes, and distribution of decay rates.

Here is an example code snippet that demonstrates how to perform global analysis on fluorescence decay curves in MATLAB using the exponential decay model:

main.m
% Step 1: Load fluorescence decay curve data
data = load('decay_curves.txt'); % Assuming the data is stored in a file

% Step 2: Convert to frequency domain using Fourier transform
freq_data = fft(data);

% Step 3: Define exponential decay model
exp_decay = @(params, t) params(1) * exp(-params(2) * t);

% Step 4: Define objective function
residuals = @(params) freq_data - exp_decay(params, t);

% Step 5: Perform fitting using lsqcurvefit
initial_params = [1, 0.1]; % Initial guess for model parameters
fitted_params = lsqcurvefit(residuals, initial_params, t, freq_data);

% Step 6: Perform global analysis by concatenating data and residuals

% Step 7: Run fitting algorithm on concatenated data

% Step 8: Analyze fitted parameters
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Note that this is a simplified example, and depending on the complexity of your fluorescence decay curves and models, you may need to modify and expand this code accordingly.