Finite-control-set model predictive control (FCS-MPC) shows great control performance and adaptability for different converter topologies and operating modes. However. The computation burden increases significantly fo...
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To forestall over the top possibly destructive block, electrical lines frequently used to convey the energy are for the most part situated under the ground in metropolitan regions. Accordingly, diagnosing the specific...
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Artificial intelligence (AI) has made it possible to improve student engagement in the learning environment in many ways, including fusing the adaptive, individualized support of AI assistants with the motivating elem...
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Recent advancements in deep learning methods encouraged researchers to apply them to process 3D objects. Initially, convolutional neural networks which have shown their ability in the processing of 2D images were used...
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We introduce a new method for robust beamforming, where the goal is to estimate a signal from array samples when there is uncertainty in the angle of arrival. Our method offers state-of-the-art performance on narrowba...
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ISBN:
(数字)9798350365504
ISBN:
(纸本)9798350365511
We introduce a new method for robust beamforming, where the goal is to estimate a signal from array samples when there is uncertainty in the angle of arrival. Our method offers state-of-the-art performance on narrowband signals and is naturally applied to broadband signals. Our beamformer operates by treating the forward model for the array samples as unknown. We show that the “true” forward model lies in the linear span of a small number of fixed linear systems. As a result, we can estimate the forward operator and the signal simultaneously by solving a bilinear inverse problem using least squares. Our numerical experiments show that if the angle of arrival is known to only be within an interval of reasonable size, there is very little loss in estimation performance compared to the case where the angle is known exactly.
In this work, we present a gaze prediction model for Virtual Reality task-oriented environments. Unlike past work which focuses on gaze prediction for specific tasks, we investigate the role and potential of temporal ...
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The deployment of deep neural networks (DNNs) on resource-constrained edge devices such as field-programmable gate arrays (FPGAs) requires a careful balance of latency, power, and resource usage while maintaining high...
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We propose a novel characterization of piecewise-defined barrier functions for certifying forward invariant sets of piecewise continuous dynamical systems. Forward invariance is established by checking two conditions:...
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ISBN:
(数字)9798350382655
ISBN:
(纸本)9798350382662
We propose a novel characterization of piecewise-defined barrier functions for certifying forward invariant sets of piecewise continuous dynamical systems. Forward invariance is established by checking two conditions: the first condition is a usual barrier-type inequality on the interior of each piece, and the second condition imposes an appropriate interaction of the tangent cone and vector field at the boundary between pieces. We then show that this separation is especially well suited for constructing discontinuous barrier functions that are an appropriate generalization of high-order control barrier functions to the piecewise setting and can be used to construct controllers for forward invariance. In particular, the tangent cone condition at the boundary of pieces does not depend on the particular control strategy and can be checked, e.g., offline, while standard online methods can be used to enforce the barrier-type inequality on the interior of pieces.
Optimizing the battery life for the miniaturized wearable devices, residing around the human body has been one of the cardinal aspects that drive the research for an energy-efficient communication medium in a Wireless...
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ISBN:
(数字)9798350351057
ISBN:
(纸本)9798350351064
Optimizing the battery life for the miniaturized wearable devices, residing around the human body has been one of the cardinal aspects that drive the research for an energy-efficient communication medium in a Wireless-Body Area network (WBAN). Wearable devices, communicating via radio frequency (RF)-based techniques incur higher losses and suffer from security vulnerabilities owing to their radiative nature. Since its emergence, Human Body Communication (HBC) has shown great promise by providing an energy-efficient and physically secure mode for information exchange among the wearable devices in the Electro-Quasistatics (EQS) frequency regime, which has been broadly explored. Besides, three regions in the body-channel characteristics namely EQS, Body Resonance (BR), and Device Resonance (DR), over a wide range of frequencies (100kHz-1GHz), have been conceptualized. With its high channel gain (CG) and bandwidth (BW), the BRHBC can potentially exhilarate high data rate body-centric communications with wearable devices. However, the HBC channel in the BR regime that contributes to its high CG and BW demands an analysis of the influence of the body-tissue properties on the channel characteristics. This paper, for the first time, studies the effect of the electrical properties of the human body as a communication medium in the BR regime. Finite Element Method (FEM) based electromagnetic (EM) simulations and wearable-to-wearable (W-W) measurements are performed to study the channel variability with the electrical properties of the communication medium during its interaction with electromagnetic fields. Results are analyzed to develop an understanding of the EM-wave propagation in the vicinity of biological materials for biomedical applications.
State-of-the-art approaches have been enabled by neural networks to attain accurate results on tasks such as detection of objects which are related to computer vision, but the success of these approaches relies on com...
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