Deep learning is a powerful tool for data mining, which uses its unsupervised learning process and multilayer network structure to automatically extract the features from complex big data. Its motivation is to establish and simulate the neural network of the human brain for analysis and learning, which simulates the mechanism of the human brain to interpret data.

Deep learning methods are an important machine learning technology. However, there are some defects in current deep learning methods – for example, they are currently consuming. Therefore, it is important to study advanced deep learning methods and their applications in online monitoring and health assessment.

This Special Issue intends to publish original research and review articles on all aspects of theoretical and applied investigations concerning deep learning methods for online monitoring and health assessment. We welcome articles that focus on advanced deep learning methods for online monitoring and health assessment in mechanical devices, new semi-supervised classification methods, and new data analysis and mining methods based on deep learning networks. Original research and review articles related to the above themes are both welcome.

Potential topics include but are not limited to the following:

• Advanced deep learning methods
• Deep learning methods for online monitoring and health assessment in mechanical devices
• New semi-supervised classification methods
• New data analysis and mining methods based on deep learning networks
• New sparse auto-encoding algorithms in deep learning
• New deep feed-forward networks
• New deep stacking networks
• New regression methods based on deep learning networks
• New unsupervised learning methods
• Online monitoring and health assessment systems based on deep learning