Basic questions on conv function
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Hi,
Suppose I have the following code:
t=(-1:.1:5); %Time axis
for i=1:1:length(t);
if t(i)<0
a=0;
h(i)= 0;
f(i) = 0;
else
a=1;
h(i) = a.*exp(-2.*t(i));
f(i) = a.*exp(-t(i)./2);
end
end
u=conv(f,h,'same')*.1;
plot(t,h,t,f,t,u1)
I'm just trying to plot the convolution of these two basic functions. When I look at examples people just use conv and plot the data along with the original functions. But it doesn't seem that easy, the convolution set is larger than the original dataset, and it's shifted. By shifted I mean the plot of conv vs. t has amplitude before t=0. How does one correct for such things to display the functions and the convolution on the same graph?
Thanks a lot, Charles
3 个评论
Angus
2013-6-25
Also this explanation and example might be helpful. The example at the end is similar to what you are doing.
Cheers
采纳的回答
Senaasa
2013-6-26
2 个评论
Michael Reshko
2019-4-4
Could you please clarify what should be done.? Say I have two Gaussian PDFs, f, sampled on interval [-a, a]. What should be the x-axis values after conv(f,f)? Thanks
Image Analyst
2019-4-4
Your first element will now corresponse to -a - a or -2a since the kernel goes more into the negative. So what was 0 no longer is at the a'th element, it's at the 2a'th element. Make adjustments if your array has more than 1 per element, but a fractional amount or something more than 1.
更多回答(3 个)
Image Analyst
2013-6-26
You need to understand both what it's doing, and what you want. If you don't want data where the kernel is not completely overlapped with the main signal, then you can use the 'valid' option. If you want it to end when it's half overlapped, use the 'same' option. Most often I use the 'same' option because I want the data the same size as the original and don't really care too much what happens out near the edges. If you want the full convolution then you have to realize that the index no longer corresponds to the same part of the signal as the same number index did in the original signal. So if you're plotting, you have to take that into account.
sri sutha
2017-3-8
I have use 13 convolutional layers for text extraction . please help me to write the coding.
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