Abstract: The application of robotic puncture system in thoracic-abdominal puncture (TAP) surgery has been hindered by the undistinguished accuracy on account of the respiratory motion. In order to ...
Abstract: Grid synchronization algorithms are of great importance in the control of grid-connected power converters, as fast and accurate detection of the grid voltage parameters is crucial in order ...
Abstract: This paper deals with a resonant gate-drive circuit for fast-switching and high-voltage power semiconductor devices, which is equipped with optical fibers for both gate control signal and dc ...
Abstract: In this article, a general introduction to the area of sensor array and multichannel signal processing is provided, including associated activities of the IEEE Signal Processing Society (SPS ...
Abstract: We propose a surrogate-assisted reference vector guided evolutionary algorithm (EA) for computationally expensive optimization problems with more than three objectives. The proposed ...
Abstract: Intensity inhomogeneity often occurs in real-world images, which presents a considerable challenge in image segmentation. The most widely used image segmentation algorithms are region-based ...
Abstract: This paper presents a flexible capacitive tactile sensor array embedded with a truncated polydimethylsiloxane pyramid array as a dielectric layer. The proposed sensor array has been ...
Abstract: Similar to the efforts to move toward electric vehicles, much research has focused on the idea of a more electric aircraft (MEA). The motivations for this research are similar to that for ...
Abstract: Bearing fault diagnosis is of significance to ensure the safe and reliable operation of a motor. Deep learning provides a powerful ability to extract the features of raw data automatically.
Abstract: In this letter, the support vector machine (SVM) regression approach is introduced to model the three-dimensional (3-D) high density microwave packaging structure. The SVM is based on the ...
Abstract: In this article, we propose a sparse spectra graph convolutional network (SSGCNet) for epileptic electroencephalogram (EEG) signal classification. The goal is to develop a lightweighted deep ...
Abstract: Large Language Models (LLMs) recently demonstrated extraordinary capability in various natural language processing (NLP) tasks including language translation, text generation, question ...