I am a beginner in AI methods. I have a collection of x(t) data, where x are some signal amplitudes and t is a time. My testing data are divided into two classes, say those from good and bad experimental samples. I need to classify the signals from unknown samples as good or bad according to their similarity to these two classes. What kind of a neural network is the best in this case? Could you recommend me some example in the literature where such a problem is considered?
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1$\begingroup$ RNN is the usual NN in case of variable length sequences as temporal ones. $\endgroup$ – pasaba por aqui Oct 21 at 14:49
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$\begingroup$ @pasabaporaqui Thank you. $\endgroup$ – Marek Oct 21 at 15:27
