Signal classifications using neural networks
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Hello , can anyone help me with ideas about how to classify different time series signals using neural networks?
Are there any single input , single output classification network? For instance lets say I have some signals-
y1 = A1*sin(2*pi*f1*t);
y2 = A2*sin(2*pi*f2*t);
y3 = A3*sin(2*pi*f3*t)+A3*sin(2*pi*f4*t);
These signals are different in amplitude and frequencies. Can a neural network be designed that can classify these three type of signals in three different class?
Training -
Input Target
y1 ------- 1
y2 ------- 2
y3 ------- 3
Now I want to test some arbitrary signal and see if the network can classify it correctly. At least frequency wise.
Thanks in advance
1 Commento
Greg Heath
il 25 Nov 2013
Are the amplitudes and frequencies known?
What is the dimensionality of the input vector?
An FFT approach might be more fruitful.
Risposte (1)
mae
il 29 Apr 2016
i am having a similar issue .. i want to use neural networks for ECG signal classification and i am stuck
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