If I feed signals at given conditions, can machine learning predict how the signal at a certain condition would look like?

Hello

I have a mixed signal separation problem where I can provide the individual signals (or their stft) at certain conditions. If I want to predict what their mixed signal output would look like at a given condition, is that possible using machine mearning?

Answer 1

[Pratik]

Hi Nasrin,

As per my understanding, you have a signal and using machine learning the mixed signal output has to be predicted.

Machine learning, especially deep learning models, can be very effective in predicting how the mixed signal output would look like at a given condition, given individual signals (or their Short-Time Fourier Transform (STFT)) at certain conditions. The problem can be approached by following steps:

1. First prepare your signals, possibly using their STFT for better model learning. You can mix individual signals to create training data if needed.
2. Then, choose a suitable machine learning model, like CNNs or LSTMs for recognizing patterns or Autoencoders and GANs for more complex tasks.
3. Train your model with these signals, using supervised methods if you have exact signal pairs, or try unsupervised methods otherwise.
4. Finally, test your model's accuracy with new data to see how well it predicts mixed signals.

Please refer to the following documentation which demonstrates an example of prediction of time series data using LSTM:

https://www.mathworks.com/help/deeplearning/ug/time-series-forecasting-using-deep-learning.html

I hope this helps!