Abstract: This paper presents robust virtual inertia control of an islanded microgrid considering high penetration of renewable energy sources (RESs). In such microgrids, the lack of system inertia ...

Abstract: Feature extraction is of significance for hyperspectral image (HSI) classification. Compared with conventional hand-crafted feature extraction, deep learning can automatically learn features ...

Abstract: We present a mixer-duplexer-antenna leaky-wave system based on periodic space-time modulation. This system operates as a full transceiver, where the upconversion and downconversion mixing ...

Abstract: Many modern object detectors demonstrate outstanding performances by using the mechanism of looking and thinking twice. In this paper, we explore this mechanism in the backbone design for ...

Abstract: A microgrid is considered to be a smart power system that can integrate local renewable energy effectively. However, the intermittent nature of renewable energy causes operating pressure and ...

Abstract: Intelligent reflecting surface (IRS) is an enabling technology to engineer the radio signal propagation in wireless networks. By smartly tuning the signal reflection via a large number of ...

Abstract: Classroom learning behavior recognition can provide effective technical support for teaching and learning. However, in natural classroom teaching scenarios, classroom learning behaviors are ...

Abstract: Recently, it was shown that a dual- or triple-band patch antenna can be designed by cutting U-slots in the patch of a broadband antenna, and the method was applied to the L-probe fed patch, ...

Abstract: Low-light raw image denoising is an essential task in computational photography, to which the learning-based method has become the mainstream solution. The standard paradigm of the ...

Abstract: The detection, diagnostic, and prognostic of bearing degradation play a key role in increasing the reliability and safety of electrical machines, especially in key industrial sectors. This ...

Abstract: The surge in global population is compelling a shift toward smart agriculture practices. This coupled with the diminishing natural resources, limited availability of arable land, increase in ...

Abstract: This paper considers cooperative kinematic control of multiple manipulators using distributed recurrent neural networks and provides a tractable way to extend existing results on individual ...