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Gate-all-around (GAA) nanowire (NW) field-effect transistor (FET) is a promising device architecture due to its superior gate controllability than that of the conventional FinFET architecture. The significantly higher electron mobility of…
Diffractive optical neural networks (DONNs) have demonstrated unparalleled energy efficiency and parallelism by processing information directly in the optical domain. However, their computational expressivity is constrained by static,…
Much effort has been devoted to device and materials engineering to realize nanoscale resistance random access memory (RRAM) for practical applications, but there still lacks a rational physical basis to be relied on to design scalable…
Coherent control of the spatial properties of light is central to a wide variety of applications from high bandwidth quantum and classical communication to high power fiber lasers. Low-loss conversion amongst a complete and orthogonal set…
Gunn (or Gunn-Hilsum) Effect and its associated negative differential resistivity (NDR) emanates from transfer of electrons between two different energy bands in a semiconductor. If applying a voltage (electric field) transfers electrons…
Learning policy from offline datasets through offline reinforcement learning (RL) holds promise for scaling data-driven decision-making while avoiding unsafe and costly online interactions. However, real-world data collected from sensors or…
Matrix differential Riccati equation (DRE) typically exhibits transient and steady-state phases, posing challenges for fixed-step time integration methods, which may lack accuracy during transients or oversample in steady regimes. In this…
Solution processed polymers are at the core of organic electronics. Polyradicals (polymers in which each repeating unit contains an unpaired spin) are unique alternatives to their p-conjugated, semiconducting counterparts. Unique of…
Autoencoders are unsupervised neural networks that are used to process and compress input data and then reconstruct the data back to the original data size. This allows autoencoders to be used for different processing applications such as…
Understanding the system-level spectral immittance response of capacitive energy storage devices with analytically tractable physics-based models is not only important for the progress of the technology, but also allows to develop new…
In this paper we first show that dynamic switching schemes can be used to reduce energy dissipation below the thermodynamic minimum of NkTlnr (N= number of state variables, 1/r=error probability), but only at the expense of the error…
In this paper, the adoption of an intelligent reflecting surface (IRS) for multiple single-antenna source terminal (ST)-DT pairs in two-hop networks is investigated. Different from the previous studies on IRS that merely focused on tuning…
As more the communications and signal process we use in the today life the more we intend to develop more reliable devices which gives fewer errors due to transient fault, So we use a technique called 5-modular redundancy to generate fewer…
When it comes to wild conditions, Facial Expression Recognition is often challenged with low-quality data and imbalanced, ambiguous labels. This field has much benefited from CNN based approaches; however, CNN models have structural…
Multirotors play a significant role in diverse field robotics applications but remain highly susceptible to actuator failures, leading to rapid instability and compromised mission reliability. While various fault-tolerant control (FTC)…
Neural population activity is theorized to reflect an underlying dynamical structure. This structure can be accurately captured using state space models with explicit dynamics, such as those based on recurrent neural networks (RNNs).…
This paper presents comprehensive studies on frequency response optimized integrators considering second order derivative regarding their numerical error, numerical stability and transient performance. Frequency domain error analysis is…
Two-dimensional (2D) materials are particularly attractive to build the channel of next-generation field-effect transistors (FETs) with gate lengths below 10-15 nm. Because the 2D technology has not yet reached the same level of maturity as…
In this work, we simulate the expected device performance and the scaling perspectives of Carbon nanotube Field Effect Transistors (CNT-FETs), with doped source and drain extensions. The simulations are based on the self-consistent solution…
Recurrent Neural Networks were, until recently, one of the best ways to capture the timely dependencies in sequences. However, with the introduction of the Transformer, it has been proven that an architecture with only attention-mechanisms…