- Try to test your LSTM network in MATLAB first. Does it match the validation data. If it does, then the issue is with a Simulink model.
- If your validation data in Simulink does not start at time 0, you need to reset the state of LSTM in State and Predict block by putting this block into a resettable subsystem and triggering it before your data starts. Ie. if your data starts at t-0.2, then do a step from 0 to 1 at 0.1 sec and feed that into reset port of resettable susbystem to reset the state.
Deep learning Toolbox - LSTM Training
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I am building an LSTM ROM to integrate into my Simscape model, which is using training and test data captured in ANSYS Chemkin software.
I have had multiple issues with pre-processing the data, which I am working through, that main reason being is ANSYS only uses a variable step solver.
I am basing my code on the LSTM ROM example. The validation of the LSTM model (before we integrate into the full Simscape model) will have to be a simple model using the "Stateful Predict" block, and then using the test and train data captured in the workspace to comapre to the LSTM model, using "From Workspace" array block to get the signals into Simulink.
I have been able to run the code, and the training progress seems that the model has minimised the RMSE and loss, however, when I try to run my simple validaton model the results show something else!, see below.
As I am unsure as to how to proceed with debugging, I am unsure whether it is the pre-processed data (which may need resampling), the LSTM network and parameter selection or the validation model that is the main cause.
My question is, can I now use the Deep Network Designer app to help debugging. Now using the code generated the concatenated data is now in a 10x1 cell, can I now save this as a datastore and use the app to train the network?
I can show the training progress, data structure and validation output below.
Validation Results: Test data top row, LSTM data bottom row.
Any suggestions on how to proceed would be great, as stuck as to how to proceed.
Thanks in advance,
Arkadiy Turevskiy on 2 Sep 2022