neural network to detect points in signal

i have two signals they look like sine wave but with some noise . in this signals of length 100 each i have 1-5 points each time(caqn change) i want to detect. my question is can i use neural network to detect points. i want network will have 2* 100 inputs which represent signal and 100 outputs which can be 1 or 0. the issue that each time i have different signals and the point location is different is it possible to design such network

Answer 1

[Greg Heath]

You don't need the complexity of a neural network.

Just use something like

d = 5
y = zeros(1,100);
for i = 1:100-d
   if sae(x1(i:i+d)-x2(i:i+d)) > thresh
   y(i+d) = 1
   end
end

Hope this helps.

Thank you for formally accepting my answer

Greg

Answer 2

[michael scheinfeild]

more complex example . the marked lines are outputs as one. they represent some stage of system which marked manually as ground truth. if i use if then else condition's it will be to large

[Greg Heath]

I don't fully understand your comment. However if you are complaining that multiple outputs have to be compared to multiple ground truth standards, then I feel for you.

Good Luck,

Greg