Sparse identification of nonlinear dynamical systems is an important project, directly addressing the physics community’s long-standing goal of data-driven discovery. Although many effective methods ...
Abstract: Standard bifacial photovoltaic (PV) panels are normally installed with fixed or seasonally adjustable tilt angles, so they can’t fully take advantage of the dynamic changes in solar ...
Abstract: This paper proposes a novel trajectory tracking model predictive control (MPC) method leveraging deep neural network-based Koopman operator theory. Specifically, the approach employs a ...
This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...
Tendon-Driven Continuum Robots are widely recognized for their flexibility and adaptability in constrained environments, making them invaluable for most applications, such as medical surgery, ...
Contributed by Shing-Tung Yau; received January 29, 2024; accepted July 19, 2024; reviewed by Stephan Huckemann and Jingyi Jessica Li Single-cell RNA sequencing (scRNA-seq) analysis, crucial for ...
The phenotypic age of the human brain, as revealed via deep learning of anatomic magnetic resonance images, reflects patterns of structural change related to cognitive decline. Our interpretable deep ...
Transformer is one of the important components of the power system, capable of transmitting and distributing the electricity generated by renewable energy sources. Dissolved Gas Analysis (DGA) is one ...
Figure 1: We present the scatter relationship between the performance weighted F-measure and parameters of all competitors on the CAMO-Test. These scatters are in various colors for better visual ...
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