How did you decide the number of hidden layers to be 32. Can you please explain this?

[sidharthgurbani]

You have 128 readings in every window. How will these input values go into the LSTRM network? I am trying to follow similar logic for my own generated dataset. So I need to understand the logic to implement for my dataset.

[guillaume-chevalier]

How did you decide the number of hidden layers to be 32. Can you please explain this?

As of having tried ANNs and RNNs on other datasets before, I know that with this quantity of data, this amount of hidden layer would be good. In practice, I've tried a few ones before settling on one. You could use this to speed up this process of finding the best parameters: https://www.neuraxle.org/stable/hyperparameter_tuning.html

You have 128 readings in every window. How will these input values go into the LSTM network?

Using Perceptrons and a 3D cube. Values are normalized and inputted to the perceptrons of the LSTM. The axis of time is well separated as a specific dimension in the 3D cube.