I am working on series prediction by LSTM-RNN.
In the training stage, I use a random series (white noise ) as input to go through a system and get the output. LSTM is implemented to learn the relationsihp between this pair of input and output. I was wondering is this mapping can be learned by LSTM as it looks the input is random but the ouput is under some physical law.
And in the testing stage, I use another type of input, for example, sine wave. Can I expect a reasonable output via the LSTM-RNN model I built in the training stage?