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RFI Mitigation for One-bit UWB Radar Systems
Radio frequency interference (RFI) mitigation is critical to the proper operation of ultra-wideband (UWB) radar systems since RFI can severely degrade the radar imaging capability and target detection performance. In this paper, ... Read More >
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EEG-based Texture Roughness Classification in Active Tactile Exploration with In ...
During daily activities, humans use their hands to grasp surrounding objects and perceive sensory information which are also employed for perceptual and motor goals. Multiple cortical brain regions are known to be responsible fo ... Read More >
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Equivariant Spherical Deconvolution: Learning Sparse Orientation Distribution Fu ...
We present a rotation-equivariant unsupervised learning framework for the sparse deconvolution of non-negative scalar fields defined on the unit sphere. Spherical signals with multiple peaks naturally arise in Diffusion MRI (dMR ... Read More >
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Identification of Phase-Locked Loop System From Its Experimental Time Series
Phase-locked loops (PLLs) are now widely used in communication systems and have been a classic system for more than 60 years. Well-known mathematical models of such systems are constructed in a number of approximations, so quest ... Read More >
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Enhanced Magnetic Resonance Image Synthesis with Contrast-Aware Generative Adver ...
A Magnetic Resonance Imaging (MRI) exam typically consists of the acquisition of multiple MR pulse sequences, which are required for a reliable diagnosis. Each sequence can be parameterized through multiple acquisition parameter ... Read More >
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Do End-to-End Speech Recognition Models Care About Context?
The two most common paradigms for end-to-end speech recognition are connectionist temporal classification (CTC) and attention-based encoder-decoder (AED) models. It has been argued that the latter is better suited for learning a ... Read More >
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Performance Dependency of LSTM and NAR Beamformers With Respect to Sensor Array ...
Prediction and nullifying the interference is a challenging problem in vehicle to infrastructure scenarios . The implementation of practical V2I network is limited because of inevitability of interference due to random nature of ... Read More >
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CheXternal: Generalization of Deep Learning Models for Chest X-ray Interpretatio ...
Recent advances in training deep learning models have demonstrated the potential to provide accurate chest X-ray interpretation and increase access to radiology expertise. However, poor generalization due to data distribution sh ... Read More >
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A Polynomial Chaos Approach to Robust $\mathcal{H}_\infty$ Static Output-Feedbac ...
This article considers the $\mathcal{H}_\infty$ static output-feedback control for linear time-invariant uncertain systems with polynomial dependence on probabilistic time-invariant parametric uncertainties. By applying polynomi ... Read More >
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Supporting More Active Users for Massive Access via Data-assisted Activity Detec ...
Massive machine-type communication (mMTC) has been regarded as one of the most important use scenarios in the fifth generation (5G) and beyond wireless networks, which demands scalable access for a large number of devices. While ... Read More >