Abstract: In this paper, we propose a data-driven supplementary control approach with adaptive learning capability for air-breathing hypersonic vehicle tracking control based on action-dependent ...
Abstract: Both objective optimization and constraint satisfaction are crucial for solving constrained multiobjective optimization problems, but the existing evolutionary algorithms encounter ...
Abstract: Following the great success of deep convolutional neural networks (CNNs) in computer vision, this paper proposes a complex-valued CNN (CV-CNN) specifically for synthetic aperture radar (SAR) ...
Abstract: This article considers an adaptive fuzzy control problem for nonstrict-feedback nonlinear stochastic systems, which contain input delay, output constraints, and unknown control coefficients, ...
Abstract: In this paper, an inductor–inductor–capacitor (LLC) resonant dc–dc converter design procedure for an onboard lithium-ion battery charger of a plug-in hybrid electric vehicle (PHEV) is ...
Abstract: Large Language Models (LLMs) recently demonstrated extraordinary capability in various natural language processing (NLP) tasks including language translation, text generation, question ...
Abstract: A kind of transmission–reflection-integrated elements and metasurfaces (MSs) are proposed to achieve full-space manipulation of amplitudes, phases, and polarization states of electromagnetic ...
Abstract: Mitigating power quality issues in distribution systems is of utmost importance to both electricity consumers and suppliers as it improves the distribution system’s efficiency, reduces ...
Abstract: The Lee sigma filter was developed in 1983 based on the simple concept of two-sigma probability, and it was reasonably effective in speckle filtering. However, deficiencies were discovered ...
Abstract: In the presence of metal implants, metal artifacts are introduced to x-ray computed tomography CT images. Although a large number of metal artifact reduction (MAR) methods have been proposed ...
Abstract: The purpose of this article is to present a novel backstepping-based adaptive neural tracking control design procedure for nonlinear systems with time-varying state constraints. The designed ...
Abstract: Clarification of the responsibility for carbon emission is fundamental in a carbon-constrained world. Existing statistical methods for carbon emission estimation usually attribute the ...
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