Related papers: Low-frequency noise parameter extraction method fo…
We present a novel direction-aware feature-level frequency decomposition network for single image deraining. Compared with existing solutions, the proposed network has three compelling characteristics. First, unlike previous algorithms, we…
This paper investigates the effect of process variations on unity gain frequency (ft) in 30 nm gate length FinFET by performing extensive TCAD simulations. Six different geometrical parameters, channel doping, source/drain doping and gate…
Lightweight online detection of series arc faults is critically needed in residential and industrial power systems to prevent electrical fires. Existing diagnostic methods struggle to achieve both rapid response and robust accuracy under…
This paper introduces FSL-HDnn, an energy-efficient accelerator that implements the end-to-end pipeline of feature extraction, classification, and on-chip few-shot learning (FSL) through gradient-free learning techniques in a 40 nm CMOS…
The extraction of spatial-temporal features is a crucial research in transportation studies, and current studies typically use a unified temporal modeling mechanism and fixed spatial graph for this purpose. However, the fixed spatial graph…
The gravitational wave detection problem is challenging because the noise is typically overwhelming. Convolutional neural networks (CNNs) have been successfully applied, but require a large training set and the accuracy suffers…
We report on transport properties of monolayer graphene with a laterally modulated potential profile, employing striped top gate electrodes with spacings of 100 nm to 200 nm. Tuning of top and back gate voltages gives rise to local charge…
We propose Graphene Klein tunnel transistors (GKTFET) as a way to enforce current saturation while maintaining large mobility for high speed radio frequency (RF) applications. The GKTFET consists of a sequence of angled graphene p-n…
In this letter, we analyze the carrier transit delay in graphene field-effect transistors (GFETs). GFETs are fabricated at the wafer-scale on sapphire substrate. For a device with a gate length of 210 nm, a current gain cut-off frequency fT…
This paper presents a comparison of several Convolutional Neural Network (CNN) models for extracting target signals in highly noisy measurement conditions. Four CNN architectures were investigated. The first comprises six consecutive…
The quality of graphene in nanodevices has increased hugely thanks to the use of hexagonal boron nitride as a supporting layer. This paper studies to which extent hBN together with channel length scaling can be exploited in graphene field…
Building compact convolutional neural networks (CNNs) with reliable performance is a critical but challenging task, especially when deploying them in real-world applications. As a common approach to reduce the size of CNNs, pruning methods…
Previous unsupervised domain adaptation methods did not handle the cross-domain problem from the perspective of frequency for computer vision. The images or feature maps of different domains can be decomposed into the low-frequency…
Text-attributed Graphs (TAGs) are commonly found in the real world, such as social networks and citation networks, and consist of nodes represented by textual descriptions. Currently, mainstream machine learning methods on TAGs involve a…
This paper addresses the standard generalized likelihood ratio test (GLRT) detection problem of weak signals in background noise. In so doing, we consider a nonfluctuating target embedded in complex white Gaussian noise (CWGN), in which the…
The signal to noise ratio (SNR) is one of the important measures for reducing the noise.A technique that uses a linear prediction error filter (LPEF) and an adaptive digital filter (ADF) to achieve noise reduction in a speech and image…
The development of flexible electronics operating at radio-frequencies (RF) requires materials that combine excellent electronic performance and the ability to withstand high levels of strain. In this work, we fabricate graphene…
Most Graph Neural Networks (GNNs) propagate messages by treating node embeddings as holistic feature vectors, implicitly assuming uniform relevance across feature dimensions. This limits their ability to selectively transmit informative…
We measured the conductance fluctuation of bi- and trilayer graphene devices prepared on mechanical exfoliated graphene by an all-dry, lithography-free process using an ultrathin quartz filament as a shadow mask. Reproducible fluctuations…
Next-generation (5G/6G) wireless systems demand low-power mm-wave phased-array ICs. Variable-gain LNAs (VGLNAs) are key building blocks enabling hardware complexity reduction, performance enhancement and functionality extension. This paper…