Abstract: The Model Predictive Control (MPC) has become a widely used technique in power converters for its simplicity and intuitive algorithm. However, for topologies with a high number of operating ...

Overview A mix of beginner and advanced-level books to suit various learning needs.Each book blends theory with practical code examples for real-world applicati ...

These computers run off human neurons. Their developers believe they are the future of artificial intelligence.

Artificial intelligence has taken many forms over the years and is still evolving. Will machines soon surpass human knowledge ...

Deep learning approaches, particularly convolutional neural networks (CNNs) and other architectures, were used in 49 papers. These models excel at image-based tasks such as land cover classification, ...

A simulation model for the digital reconstruction of 3D root system architectures. Integrated with a simulation-based inference generative deep learning model.

A recent Nature study shows that separated artificial neural networks can accurately model SiC MOSFETs using minimal training data. Silicon carbide MOSFETs are increasingly replacing traditional ...

Abstract: Spiking neural networks (SNNs) can be operated in an event-driven manner to save energy consumption of artificial neural networks (ANNs), which has attracted enormous research interests for ...

Department of Materials Science and Engineering, City University of Hong Kong, Kowloon 999077, Hong Kong China Department of Physics, City University of Hong Kong, Kowloon 999077, Hong Kong China ...

A comprehensive neural network project built with PyTorch and managed with UV for fast Python package management. neural-network-project/ ├── src/ │ ├── models/ # Neural network model definitions │ │ ...