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Time Series and Sequence Data Networks

Deploy networks trained for time series classification, regression, and forecasting tasks to target FPGA and SoC boards

You can train and deploy networks to do time series classification, regression, and forecasting tasks by using long short-term memory (LSTM) networks. An LSTM is a type of recurrent neural network (RNN) that can learn long-term dependencies between time steps of sequence data. Learn about:

  • Support for LSTM networks.

  • How Deep Learning HDL Toolbox™ compiles the LSTM layer in a network.

  • How to deploy LSTM networks to target FPGA and SoC boards, then use Deep Learning HDL Toolbox and MATLAB to retrieve the prediction results from the network.


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dlhdl.WorkflowConfigure deployment workflow for deep learning neural network (Since R2020b)
dlhdl.TargetConfigure interface to target board for workflow deployment (Since R2020b)


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releaseRelease the connection to the target device (Since R2020b)
validateConnectionValidate SSH connection and deployed bitstream (Since R2020b)
activations Retrieve intermediate layer results for deployed deep learning network (Since R2020b)
compile Compile workflow object (Since R2020b)
deploy Deploy the specified neural network to the target FPGA board (Since R2020b)
predictPredict responses by using deployed network (Since R2020b)
predictAndUpdateState Predict responses by using a trained and deployed recurrent neural network and update the deployed network state (Since R2022b)
resetState Reset state parameters of deployed neural network (Since R2022b)