A 5G wireless system requests a high-performance compact antenna *** research work aims to report the characterization and verification of the artificial magnetic conductor(AMC)metamaterial for a high-gain planar *** ...
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A 5G wireless system requests a high-performance compact antenna *** research work aims to report the characterization and verification of the artificial magnetic conductor(AMC)metamaterial for a high-gain planar *** configuration is formed by a double-side structure on an intrinsic dielectric *** 2-D periodic pattern as an impedance surface is mounted on the top surface,whereas at the bottom surface the ground plane with an inductive narrow aperture source is *** characteristic of the resonant transmission is illustrated based on the electromagnetic virtual object of the AMC resonant structure to reveal the unique property of a magnetic material *** characteristics of the AMC metamaterial and the planar antenna synthesis are investigated and verified by experiment using a low-cost FR4 dielectric *** directional antenna gain is obviously enhanced by guiding a primary field *** loss effect in a dielectric slab is essentially studied having an influence on antenna *** verification shows a peak of the antenna gain around 9.7 dB at broadside which is improved by 6.2 dB in comparison with the primary aperture antenna without the AMC *** thin antenna profile ofλ/37.5 is achieved at 10GHz for *** emission property in an AMCstructure herein contributes to the development of a lowprofile and high-gain planar antenna for a compact wireless component.
the eyes are one of the essential organs in our body since it is the organ that gives us vision and can best protect us from danger. A pupil that dilates or constricts also corresponds with the change of its size;doct...
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Predicting drug-target interactions (DTI) has become an important step in the drug discovery and drug repositioning process. The biological identification of DTI incurs significant financial and temporal costs, and th...
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Speech is considered the most important way for communication between humans. However, various types of noise degrade speech signals and reduce speech clarity. Usually, speech should be clear as much as possible to be...
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We consider channel coding for Gaussian channels with the recently introduced mean and variance cost constraints. Through matching converse and achievability bounds, we characterize the optimal first- and second-order...
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We apply the Newton-Raphson flow tracking controller to aggressive quadrotor flight and demonstrate that it achieves good tracking performance over a suite of benchmark trajectories, beating the native trajectory trac...
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ISBN:
(数字)9798350382655
ISBN:
(纸本)9798350382662
We apply the Newton-Raphson flow tracking controller to aggressive quadrotor flight and demonstrate that it achieves good tracking performance over a suite of benchmark trajectories, beating the native trajectory tracking controller in the popular PX4 Autopilot. The Newton-Raphson flow tracking controller is a recently proposed integrator-type controller that aims to drive to zero the error between a future predicted system output and the reference trajectory. This controller is computationally lightweight, requiring only an imprecise predictor, and achieves guaranteed asymptotic error bounds under certain conditions. We show that these theoretical advantages are realizable on a quadrotor hardware platform. Our experiments are conducted on a Holybrox x500v2 quadrotor using a Pixhawk 6x flight controller and a Rasbperry Pi 4 companion computer which receives location information from an OptiTrack motion capture system and sends input commands through the ROS2 API for the PX4 software stack.
A practical restoration problem can be formulated as a multi-period mixed integer nonlinear programming (MINLP) problem, which is challenging to solve. This paper seeks to propose a novel problem formulation and prese...
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This study addresses the limitations of Transformer models in image feature extraction,particularly their lack of inductive bias for visual *** to Convolutional Neural networks(CNNs),the Transformers are more sensitiv...
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This study addresses the limitations of Transformer models in image feature extraction,particularly their lack of inductive bias for visual *** to Convolutional Neural networks(CNNs),the Transformers are more sensitive to different hyperparameters of optimizers,which leads to a lack of stability and slow *** tackle these challenges,we propose the Convolution-based Efficient Transformer Image Feature Extraction network(CEFormer)as an enhancement of the Transformer *** model incorporates E-Attention,depthwise separable convolution,and dilated convolution to introduce crucial inductive biases,such as translation invariance,locality,and scale invariance,into the Transformer ***,we implement a lightweight convolution module to process the input images,resulting in faster convergence and improved *** results in an efficient convolution combined Transformer image feature extraction *** results on the ImageNet1k Top-1 dataset demonstrate that the proposed network achieves better accuracy while maintaining high computational *** achieves up to 85.0%accuracy across various model sizes on image classification,outperforming various baseline *** integrated into the Mask Region-ConvolutionalNeuralnetwork(R-CNN)framework as a backbone network,CEFormer outperforms other models and achieves the highest mean Average Precision(mAP)*** research presents a significant advancement in Transformer-based image feature extraction,balancing performance and computational efficiency.
Inspired by many-body effects, we propose a novel design for Boltzmann machine (BM)-based invertible logic (IL) using probabilistic bits (p-bits). A CMOS-based XNOR gate is derived to serve as the hardware implementat...
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In view of the shortcomings of low accuracy and high false positive rate in the traditional anonymous network traffic analysis methods, this paper proposes the construction and experimental technologies of the anonymo...
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