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Not sure how to do a smoothing average of noisy data

11 vues (au cours des 30 derniers jours)
Jason
Jason le 19 Fév 2015
Commenté : Jason le 19 Fév 2015
Not sure how to do a smoothing average of noisy data based off what the instructions asked this is what I've come up with so far any help would be appreciated.
clear;
clc;
load('noisydata.mat','x');
N = x;
y = zeros(1,length(N));
for k = 2:1:length(x)
if (k~= 1 & k~= N)
y(k) = (x(k-1)+x(k+1))/2;
end
end

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Image Analyst
Image Analyst le 19 Fév 2015
You forgot to set y(1) = x(1) before the loop, and, after the loop, set y(length(x)) = x(end). Then have your loop go from k = 2 : (length(x)-1).
  3 commentaires
Image Analyst
Image Analyst le 19 Fév 2015
Modifié(e) : Image Analyst le 19 Fév 2015
Well I said to put y(length(x))= x(end); after the loop, not inside it.
And for some reason you plotted only a single point
plot(y(k))
instead of the whole curve:
plot(x, 'r*-');
hold on;
plot(y, 'b-', 'LineWidth', 2);
But anyway, try that, because other than that it looks like it should work. But you didn't attach noisydata.mat so I can't test it.
Jason
Jason le 19 Fév 2015
sorry about that I thought I did just attach it to this comment. I really appreciate the help to! thank you. The reason I plotted only one point was I because I wasn't sure what to compare the noisy data with, and what to compare the smoothed data with.

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Plus de réponses (1)

Geoff Hayes
Geoff Hayes le 19 Fév 2015
Jason - I think that you have correctly interpreted what the question is asking (less the plot) but you may want to reconsider the condition for your if statement
if (k~= 1 & k~= N)
Remember that k is a scalar but N is a vector/array so this comparison is not what you want. If you want to exclude the first and last elements from x then just extend what you have started with the for statement
for k = 2:1:length(x)-1
So now k ranges from 2 to one less than the length of x which is exactly which values you need to consider (and so no longer have any need for the condition).
  3 commentaires
Geoff Hayes
Geoff Hayes le 19 Fév 2015
Jason - you are being asked to plot the original noisy data versus the sample number. The sample numbers are the indices into your noisy matrix x. How would you plot this?
Jason
Jason le 19 Fév 2015
I'm not sure this whole problem has beat me down. I know its probably something simple

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