Deep reinforcement learning has shown great potential in the field of robot control, but it still faces challenges in continuous control tasks. Traditional reinforcement learning algorithms perform ...

Integrating Transformer and LSTM to encode observation before filtering, makes it easier for EM algorithm to estimate parameters. Conclusions Combining Transformer and LSTM as an encoder-decoder ...

This demo shows the full deep learning workflow for an example of signal data. We show how to prepare, model, and deploy a deep learning LSTM based classification algorithm to identify the condition ...

2.2 Deep learning model. The deep-learning algorithm used in this study is shown as Figure 2. The model comprises a gated module, a LSTM module, and a prediction module. Firstly, a gated layer is ...

Therefore, this study proposed an improved deep learning algorithm based on the load classification approach in terms of raising the classification performances with solving the data ... the precision ...

Deep learning defined. Deep learning is a form of machine learning that models patterns in data as complex, multi-layered networks. Because deep learning is the most general way to model a problem ...