相关论文: Low-frequency noise parameter extraction method fo…

Field-Effect Transistors with graphene channels or GFETs are an interesting alternative for the detection of analytes in biological fluids since the electrical behavior of the channel changes when exposed to a sample (among other detection…

We propose a novel scheme for laser phase noise measurements with minimized sensitivity to external fluctuations including interferometer vibration, temperature instability, other low-frequency noise, and relative intensity noise. In order…

Graph neural networks (GNNs) achieve strong performance on graph learning tasks, but training on large-scale networks remains computationally challenging. Transferability results show that GNNs with fixed weights can generalize from smaller…

Micro-Doppler signatures contain considerable information about target dynamics. However, the radar sensing systems are easily affected by noisy surroundings, resulting in uninterpretable motion patterns on the micro-Doppler spectrogram.…

Convolutional neural networks (CNN) have achieved impressive performance on the wide variety of tasks (classification, detection, etc.) across multiple domains at the cost of high computational and memory requirements. Thus, leveraging CNNs…

Graph Neural Networks (GNNs) have been widely employed for semi-supervised node classification tasks on graphs. However, the performance of GNNs is significantly affected by label noise, that is, a small amount of incorrectly labeled nodes…

We address the problem of recovering a signal (up to global phase) from its short-time Fourier transform (STFT) magnitude measurements. This problem arises in several applications, including optical imaging and speech processing. In this…

High frequency performance limits of graphene field-effect transistors (FETs) down to a channel length of 20nm are examined by using self-consistent quantum simulations. The results indicate that although Klein band-to-band tunneling is…

Identifiability and sloppiness are investigated in this paper for the parameters of a descriptor system based on its frequency response samples. Two metrics are suggested respectively for measuring absolute and relative sloppiness of the…

This paper aims to provide a novel design of a multiscale framelet convolution for spectral graph neural networks (GNNs). While current spectral methods excel in various graph learning tasks, they often lack the flexibility to adapt to…

Tunneling field-effect transistors (FETs) have been intensely explored recently due to its potential to address power concerns in nanoelectronics. The recently discovered graphene nanoribbon (GNR) is ideal for tunneling FETs due to its…

Low-Rank Factorization (LRF) is a widely adopted technique for compressing deep neural networks (DNNs). However, it faces several challenges, including optimal rank selection, a vast design space, long fine-tuning times, and limited…

Steel wire ropes (SWRs) are critical load-bearing components in industrial applications, yet their structural integrity is often compromised by local flaws (LFs). Magnetic Flux Leakage (MFL) is a widely used non-destructive testing method…

The influence of the channel shape in a junctionless silicon-on-insulator finned field-effect transistor (JL SOI FinFET) on the amplitude of random telegraph noise (RTN) induced by single interface trapped charge has been simulated for the…

Ubiquitous low frequency 1/f noise can be a limiting factor in the performance and application of nanoscale devices. Here, we quantitatively investigate low frequency electronic noise in single-layer transition metal dichalcogenide MoS2…

We propose a low complexity graph-based linear minimum mean square error (LMMSE) equalizer which considers both the intersymbol interference (ISI) and the effect of non-white noise inherent in Faster-than-Nyquist (FTN) signaling. In order…

1/f noise is a critical figure of merit for the performance of transistors and circuits. For two-dimensional devices (2D-FETs), and especially for applications in the GHz range where short-channel FETs are required, velocity saturation (VS)…

In this paper, an in-pixel chopping technique to reduce the low-frequency or 1/f noise of the source follower (SF) transistor in an active pixel sensor (APS) is presented. The SF low-frequency noise is modulated at higher frequencies…

Graph convolution networks (GCNs) are currently mainstream in learning with irregular data. These models rely on message passing and attention mechanisms that capture context and node-to-node relationships. With multi-head attention, GCNs…

Graphene field-effect transistors (GFETs) are among the most promising platforms for ultrasensitive chemical and biological sensing due to their high carrier mobility, large surface area, and low intrinsic noise. However, conventional…