Related papers: A compact Verilog-A ReRAM switching model
Recent considerations for reconfigurable intelligent surfaces (RISs) assume that RISs can convey information by reflection without the need of transmit radio frequency chains, which, however, is a challenging task. In this paper, we propose…
We report on resistive switching (RS) characteristics of W/WO3-x/Pt-based thin film memristors modulated by precisely controlled oxygen non-stoichiometry. RS properties of the devices with varied oxygen vacancy (VO) concentration have been…
For neuromorphic engineering to emulate the human brain, improving memory density with low power consumption is an indispensable but challenging goal. In this regard, emerging RRAMs have attracted considerable interest for their unique…
Complementary resistive switches (CRS) are considered as a potential solution for the sneak path problem in large-scale integration of passive crossbar resistive memory arrays. A typical CRS is composed of two bipolar memory cells that are…
Reduced Order Models (ROMs) are of considerable importance in many areas of engineering in which computational time presents difficulties. Established approaches employ projection-based reduction such as Proper Orthogonal Decomposition,…
Memristors are prominent passive circuit elements with promising futures for energy-efficient in-memory processing and revolutionary neuromorphic computation. State-of-the-art memristors based on two-dimensional (2D) materials exhibit…
Thermodynamic-driven filament formation in redox-based resistive memory and the impact of thermal fluctuations on switching probability of emerging magnetic switches are probabilistic phenomena in nature, and thus, processes of binary…
Resistive random access memory (RRAM) is very well known for its potential application in in-memory and neural computing. However, they often have different types of device-to-device and cycle-to-cycle variability. This makes it harder to…
Manipulating the electromagnetic (EM) reflection behavior from an arbitrary surface dynamically on arbitrary design goals is an ultimate ambition for many EM stealth and communication problems, yet it is nearly impossible to accomplish with…
Resistive-switching -- the current-/voltage-induced electrical resistance change -- is at the core of memristive devices, which play an essential role in the emerging field of neuromorphic computing. This study is about resistive switching…
The present paper develops recursive algorithms to track shifts in the resonance frequency of linear systems in real time. To date, automatic resonance tracking has been limited to non-model-based approaches, which rely solely on the phase…
Sequential recommendation aims to recommend the next item of users' interest based on their historical interactions. Recently, the self-attention mechanism has been adapted for sequential recommendation, and demonstrated state-of-the-art…
This article introduces a novel, low-cost technique for hiding data in commercially available resistive-RAM (ReRAM) chips. The data is kept hidden in ReRAM cells by manipulating its analog physical properties through switching…
Dynamic Random Access Memory (DRAM) is the de-facto choice for main memory devices due to its cost-effectiveness. It offers a larger capacity and higher bandwidth compared to SRAM but is slower than the latter. With each passing generation,…
Recently, the Edge Computing paradigm has gained significant popularity both in industry and academia. Researchers now increasingly target to improve performance and reduce energy consumption of such devices. Some recent efforts focus on…
The maximum achievable rate is derived for resistive random-access memory (ReRAM) channel with sneak path interference. Based on the mutual information spectrum analysis, the maximum achievable rate of ReRAM channel with independent and…
Resistive In-Memory Computing (RIMC) offers ultra-efficient computation for edge AI but faces accuracy degradation due to RRAM conductance drift over time. Traditional retraining methods are limited by RRAM's high energy consumption, write…
A metallic ring based, diode-integrated, low-profile, power-dependent, reflective metasurface working from 3 GHz to 3.6 GHz is proposed in this letter. Unlike the previous study which shifts a band up and down to change the impedance of the…
Artificial Recurrent Neural Networks are a powerful information processing abstraction, and Reservoir Computing provides an efficient strategy to build robust implementations by projecting external inputs into high dimensional dynamical…
RRAM technology has experienced explosive growth in the last decade, with multiple device structures being developed for a wide range of applications. However, transitioning the technology from the lab into the marketplace requires the…