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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
dlhdl.TargetConfigure interface to target board for workflow deployment


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