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How MATLAB makes the distinction between P-Cores and E-Cores?

  It is known that modern CPUs have both Performance cores (P-cores) and efficiency cores (E-cores), different types of CPU cores that have different purposes and are designed for different tasks. P-cores typically have higher clock speeds and designed for high-performance tasks, while E-cores operate at lower clock speeds and focus on energy-efficient processing. In MATLAB, maxNumCompThreads returns the current maximum number of computational threads. Currently, the maximum number of computational threads is equal to the number of physical cores on your machine. How MATLAB makes the distinction between P-Cores and E-Cores ? NOTE:- Matlabsolutions.com  provide latest  MatLab Homework Help, MatLab Assignment Help  ,  Finance Assignment Help  for students, engineers and researchers in Multiple Branches like ECE, EEE, CSE, Mechanical, Civil with 100% output.Matlab Code for B.E, B.Tech,M.E,M.Tech, Ph.D. Scholars with 100% privacy guaranteed. Get MATLAB projects...
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Finding Accurate Amplitude Using FFT

 I have been working on code to use the FFT to find the amplitude of a signal. However, despite my best efforts to window I seem to get incorrect amplitudes. When I manually find Amplitude by inspecting the signal I get A = 63.7. When I use the following code I get A = 54.8. This is causing significant errors in my Bode plot.

 
I tried using a flat top window to maximize amplitude accuracy. My signal does not seem significantly noisy. I expected an amplitude much closer to the true value.
 
function Amplitude = Gaindb(x)

 if size(x, 2) > 1
    x = x';
end

 x = x - mean(x);

 N = length(x);
 win = flattopwin(N);

 x = fft(x.*flattopwin(N));

 Amplitude = 2*max(abs(x))/N;
  end



ANSWER



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When I run your code I get 14.5 for the answer, so I am not sure how you are getting 54.8. But the 14.5 is consistent with the Matlab definition of the flattop window. From the documentation, the flattop is a sum of cosines with certain coefficients, along with a constant coefficient a0 = .216. a0, the area of the window, is basically the amplitude reduction factor for the signal.
Without any windowing of x, the fft comes up with a signal amplitude of 67.1, and 67.1 x .216 = 14.5 which is consistent.
The Matlab window peaks out at a value of 1.



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