How to create a For Loop to Loop through all the rows in the matrix
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Hello all. I am working with time series data. I have a matrix 142x240000 (142 rows, each row has 240000 columns). I want to calculate the the normalisation weight for each row. Below is the code:
%Normilisation time window width.half of the max period of the bandpass which is applied to the data prior to cross-correlation. (7Hz-40Hz)
N=0.07;
%Calculate the size of the signal to get number of columns and rows. n is number of rows and p is number of columns
[n,p] = size(signal);
%Calculate the normalised weights
count = 0
for j = 1:142 %Matrix indexing, each row representing 10 minutes
count = count + 1;
ten = 240000; %Number of columns
%Divide signal into 142 rows and 240000 columns
A(count,:) = signal(((j-1)*ten)+1:ten*j);
The above code runs just fine. It takes the signal that I have and divides it into 142 rows and 240000 columns. I now need to calculate the normalisation weight for each row. In the end, I want to have a matrix called weight with the size 142x1, each row should have the calculated weight of it's corresponding row from matrix A. The formula for calculating weight is:
weight =(1/((2*N)+1))*sum(abs(row)).
The code I have to calculate the weight is:
for i = 1:142
weight(i)=(1/((2*N)+1))*sum(abs(A)); %The A here should be the rows(row1,row2,...till row 142)
end
How do I make the For Loop to calculate the weight from row 1 to row 142 and store the calculated weights as a 142x1 matrix
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dpb
am 15 Jul. 2018
Bearbeitet: dpb
am 15 Jul. 2018
You don't need any loops at all...use the MATrix LABoratory vectorized operations. You already have the the signal in the array, you don't need anything to use it--
weight=1/(2*N+1)*sum(abs(signal),2);
The only "trick" here is to use the optional second argument to sum to add row elements (2nd dimension) instead of the default by column.
NB: The above assumes your parentheses-nesting is correct as the formula is written that the weight is intended as
wt = SUM(|signal|)/(2N+1)
and not as
wt = 1/{(2N+1)*SUM(|signal|)}
If it is instead the latter, you'll need
weight=1./((2*N+1)*sum(abs(signal),2));
using the "dot" divide operator for element-wise division.
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