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How can I detect P-R interval from an ECG signal using MATLAB ? Can anyone give me code or any steps to determine this ?
Find the P wave (s).
Find the QRS complex(es).
Pair up a QRS complex and its preceding P wave. Make sure to avoid cases where there is a PVC or other abnormal beat in between.
Subtract the time of the P wave from the time of the R peak in the QRS complex.
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Identification of brain areas after language stimuli
Hi guys, I'm trying to solve a problem with my code in matlab. My goal is to identificate brain areas associated to language stimuli. After I performed some tasks, i arrived to plot the convolution between the BOLD signal and square signal (stimuli). Now, my goal is to perform a regression using regress between the convolution result (1x481 matrix) and a matrix containing the number of voxels of my brain images (92614x39) where the rows are the voxels and 39 are the MRI scans. So, the two matrices have different size and I have no idea how to perform a regression. Anyone could help me?
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I wan to give x,y,z coordinates to a point, for example to P point.
The P point coordinates are: P=(0,1,1)
How can I give the values in Matlab?
I tried P=(0,1,1) and Px=0 Py=0 Pz=0 ,but I need it to an equation.
one variable can store n-dimensional coordinates
P=[0 1 1];
you can also do this:
px=0;
py=1;
pz=1;
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If i have data in NxN grid format (for example see figure) and each cell size is given by (Xmax/N) x (Ymax/N) and data given in each cell is the frequency data of that cell. What is the best way to graphically represent this data in MATLAB such that it is easy to view the frequency for each cell? If I would like to make it like in this example (see colormap), how can I do that what function should I used?
Your choice. Here I put several possibilities:
bar3: if you the points are discrete by meaning
surf or mesh : if the points are continuous by meaning
-imshow or image
in MATLAB 2017b or newer, heatmap
-contour, if you have a sufficiently detailed data
There may be more, please feel free to add them to the post.
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The addition of an extra term, called a proportional factor reduces the convergence of the back propagation algorithm.
So how to avoid local minima in Back propagation algorithm.
In local minimum a gradient of an error function is a zero vector - so backprop - which is using a gradient - cannot move your parameters any further and finishes training.
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I have a matrix 180*360*120.
120 is time series of temperature in kelvin. now I want to convert this temperature from kelvin to Celsius. kindly suggest me a Matlab code for this conversion.
So what I understand is that you have a matrix A of dimensions 180*360*120 i.e. having 7776000 elements of kelvin temperatures. These Kelvin you want in Celsius. Can you not simply have the following code to get the result?
B=A-273.15
where B is your matrix with temperatures in Celsius