central difference method
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abdulhadi khalifa
am 18 Apr. 2012
Bearbeitet: Muhammad Hammad Malik
am 16 Feb. 2021
How can I calculate the central difference for set of data using matlab If I have big data.Could any one help me to do it for this small data so I can I apply to my data X 0.225 0.30 0.35 0.40 0.45 0.475 Y 0.251 0.90 2.02 3.63 7.2 9.800
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Jan
am 18 Apr. 2012
You can simply use:
gradient(X, Y)
Then the first and the last element are forward and backward differences respectively. But all interior elements are central differences.
For large data sets FEX: DGradient is faster (10 to 16 times) than Matlab's gradient. In addition it can calulate the 2nd order approximation, when X is not uniformly distributed.
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Jan
am 15 Feb. 2021
t = linspace(0, 2*pi, 1000);
x = sin(t);
dx = (x(11:5:end) - x(1:5:end-10)) / (10 * diff(t(1:2)));
plot(t(1:5:end-5), cos(t(1:5:end-5)), 'ro');
hold on
plot(t(5:5:end-10),dx)
Muhammad Hammad Malik
am 15 Feb. 2021
Bearbeitet: Muhammad Hammad Malik
am 16 Feb. 2021
@Jan thanks for the kind response. i have checked your code, but unable to understand well. why you use 11:5 and cos.
pls see what i have done, i am attaching here, the issue is i am unable to add window overlap.I also can change the window size to bigger or smaller, not restricted to use just 10.
The one you mentioned is working but how i can plot that with my time vector "IMU_ULISS.time" (1x25805), and i changed this time vector to plot mine as you can see.
Grad =gradient(Data_filtered(1:window:end),window)
figure;
plot(IMU_ULISS.time(1:window:end),Grad)
time_modified=IMU_ULISS.time(1:window:end)
hold onplot(time_modified(ceil(find(IMU_ULISS.step_instant_target(1,:)>0)/window)),Grad(ceil(find(IMU_ULISS.step_instant_target(1,:)>0)/window)),'r');
hold on
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abdulhadi khalifa
am 18 Apr. 2012
1 Kommentar
Jan
am 18 Apr. 2012
The output of GRADIENT *is* the slope. See my former answer.
It would be more helpful if you reply to the different ideas you got in your other postings concerning this problem. Simply posting the problem repeatedly in new threads wastes the time of all who want to assist.
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