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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...

Why Cross Correlation (xcorr) of Two simultaneously Recorded Audio Signals Always return randomly different lags?

 Hi everyone! I'm working on a sound localization project in which I record two audio  signals simultaneously and then take their 'cross correlation' to find out the "lags" existing between the two signals! But what happens is that every time a random angle is calculated because of the abrupt values of the lags each time! I don't know where I'm going wrong! Please guide me if there is a better approach to achieve a better sound localization ! The code is given as follows:

   if true
  fs = 48000 ; %sampling frequency in Hz
  recObj1 = audiorecorder(fs, 16, 1, 1);
  recObj2 = audiorecorder(fs, 16, 1, 2);

record(recObj1);
record(recObj2);

pause(5);         % record for 5 seconds simultaneously 

stop(recObj1);
stop(recObj2);

out1 = getaudiodata(recObj1, 'int16');
out2 = getaudiodata(recObj2, 'int16');

    L = out1 ;
    R = out2 ;

t1 = (0:length(L)-1)/fs;
t2 = (0:length(R)-1)/fs;

figure;

plot(t1,L);
figure;
plot(t2,R);
 threshold = 100;

k=1;
win =200 ;
[k max(L) max(R)]
if max(L)>th && max(R)>th     %set power threshold

[c, lags] = xcorr(L, R);
[a1,b1] = max(L);
[a2, b2] = max(R);
[a3, b3] = max(c);
s = lags(b3);   
time_delay = s/fs ; 
disp(time_delay);
 s = abs(s);            % taking absolute of s

disp('Estimated angle');
 c = 342;       % avg speed of sound at room temperature
dis = 1 ;       % mean distance between the two microphones                 
cal = ((time_delay*c)/dis) ;
if cal<-1
cal=-1;
elseif cal>1
cal=1;
end
ang =((acosd(cal))

disp(ang);     %displays the angle of sound source due to these microphones

    end


ANSWER



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I work at Matlabsolutions in the Audio System Toolbox team. I can't exactly replicate your experiement as I don't have your hardware, but I could notice a few possible sources of issues.
 
In your code you seem to be acquiring  simultaneously from two different devices using the default audio drivers (typically DirectSound or WASAPI on Windows). That gives you no guarantee of synchronous acquisition for L and R. The two devices themselves may be triggered asynchronously by the operating system, giving you an arbitrary new delay between the two signals every single time you run your script.
 
The simplest guarantee of a synchronous acquisition comes from acquiring different channels of the same device, ideally using its ASIO driver instead of the default one. ASIO drivers guarantee synchronous multi-channel acquisition.

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