MISO System. LSTM

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Hello. I have a MIMO (multiple input-single output) system. Each of the two inputs has 100 random values. The only output has 100 values.
I put the entries as an array of cells:
sim_in = {v , p}';
and I pick up the output:
sim_out = {h1.Data}';
When training the network I get the error "Invalid training data. Predictors and responses must have the same number of observations." What would be the solution? Thank you.

采纳的回答

Aman
Aman 2024-4-16
Hi Jesus,
This error occurs due to a dimension mismatch between the targets and the network output.
Since you are using a MISO neural net, it is better to concatenate the inputs along the appropriate dimension and reshape your output data, as we give a single input and single output to the "trainNetwork" function.
You can refer to the thread below, which discusses the same issue.
Hoping it will help you move ahead with your workflow.

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Jesus Mª Juarez Ferreras
编辑:Jesus Mª Juarez Ferreras 2024-5-8
Hello again. Once the previous problem is solved, now I put:
sim_out = {h1.Data h1.Data}';
I want to train the MISO system that I leave in the file. I want to get the RMSE close to zero but it doesn't train well.
Does LSTM not train MISO systems?
Thanks you.

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