how do i define a convolution layer for time series data matlab

how do i define a convolution layer for time series data matlab using deep learning designer app?When i use sequence input layer before convolution layer , it shows input size mismatch error

Answer 1

[Davide Fantin]

As of MATLAB R2021a, defining a convolution layer for time series data is not directly supported in Deep Network Designer.

Currently, the 1-D convolution operation is available through the custom training loop workflow with a "model as function" approach and you can find an example available in the doc here: https://www.mathworks.com/help/deeplearning/ug/sequence-to-sequence-classification-using-1-d-convolutions.html

The Development team is aware of this limitation and will consider to address it in future releases.

Solutions that you can try:

• Recurrent Neural Network (lstmLayer, gruLayer, ...), available in Deep Network Designer App
• Adaptation of Feed-Forward Networks, i.e. folding/unfolding of sequences and a fullyConnectedLayer in between, available in Deep Network Designer App.
• Convolutional Neural Network approach as described in the aforementioned example, using a custom training loop (hence not using Deep Network Designer)

Hope this helps!

[NN]

Thank you very much .i will look into this example

Answer 2

[Girijashankar Sahoo]

Choose length of input is same as length of comvolution layer

[NN]

Thanks for the suggestion , but please let me know how i can do it .?i am attaching the layer details,which parameter should i change in accordance with number of features as in sequence input data?