I am training a Tensorflow classifier model with signal data (converting signals to the spectrograms).
I want the model to be insensitive to the arrival time of the signal within the fixed window.
Moreover the model should classify both of these signals as the same.
- Train the model using the same signal at different arrival times
- Preprocess the signal before providing it to the model
I want to avoid 1. because it will mean I have to generate a huge amount of signal data which will slow down training.
Are there any commonly applied preprocessing steps for this problem?