A5101698907- Advanced Memory and Neural Computing
- Advancements in Semiconductor Devices and Circuit Design
- Semiconductor materials and devices
- Ferroelectric and Negative Capacitance Devices
- Neural dynamics and brain function
- Neuroscience and Neural Engineering
- 2D Materials and Applications
- Neural Networks and Reservoir Computing
- Neural Networks and Applications
- Silicon Carbide Semiconductor Technologies
- Chalcogenide Semiconductor Thin Films
- Electronic and Structural Properties of Oxides
- CCD and CMOS Imaging Sensors
- Integrated Circuits and Semiconductor Failure Analysis
- Quantum and electron transport phenomena
- Quantum Computing Algorithms and Architecture
- Photoreceptor and optogenetics research
- Semiconductor materials and interfaces
- Perovskite Materials and Applications
- Thin-Film Transistor Technologies
- Advanced Condensed Matter Physics
- Phase-change materials and chalcogenides
- MXene and MAX Phase Materials
- Conducting polymers and applications
- Graphene research and applications
Anhui University
2015-2025
ETH Zurich
2021
Harbin University of Science and Technology
2013
Beijing University of Posts and Telecommunications
2011
Spiking neuron circuits, responsible for encoding analog signals into spiking signals, are crucial conversion-based neural networks (SNNs), enabling direct integration with conventional deep learning. However, the mainstream ReLU (Rectified Linear Unit) circuits lack capability to encode negative values, resulting in loss of information. In this work, a circuit featuring L-ReLU (Leaky Rectified function based on an optimized threshold switching (TS) memristor model asymmetric character was...
Abstract Artificial neurons with leaky rectified linear unit (L‐ReLU) function can effectively process negative information, enhancing the neuromorphic systems capbility to handle values. Memristive devices show great potential in building compact and bio‐plausible artificial neurons, however, a neuron device that supports L‐ReLU functions is still lacking. In this work, proposed based on bipolar asymmetrical diffusive memristor. Utilizing intercalation leveraging migration diffusion ratio...
Abstract Hybrid quantum-classical neural networks (QCNNs) integrate principles from quantum computing principle and classical networks, offering a novel computational approach for image classification tasks. However, current QCNNs with sequential structures encounter limitations in accuracy robustness, especially when dealing tasks involving numerous classes. In this study, we propose solution - the hybrid Parallel Quantum Classical Neural Network (PQCNN) This architecture seamlessly...
In this article, we analyzed the experimental data based on TaOx memristor and found that threshold switching (TS) characteristics are related to temperature, its logarithmic I–V curve is in good agreement with space charge limiting current conduction mechanism. We use mechanism establish a TS physical model then build an LTspice model. The fitted data, which basically consistent. Next, using simulate leaky integrate-and-fire neuron circuit, basic dynamics realized. By changing external...
Memristor, a nanoscale device with the advantages of simple structure, excellent scalability, and complementary metal–oxide–semiconductor (CMOS) process compatibility, has drawn extensive research attention for various applications. An appropriate memristor model is essential researcher to explore potential applications memristor-based systems. Hewlett-Packard (HP) computation complexity favorable choice simulation works. Incorporating window function into HP emulating fealty nonlinearity...
A more accurate synaptic modeling based on oxygen vacancy conductive mechanism is presented in this paper. Two internal state variables, that is, the length and area of region, are used to describe vertical lateral growth/dissolution dynamics physical mechanisms ion drift two different diffusion effects. Since effect electric field not negligible, it introduced into modeling. In addition, Fick Soret diffusions considered, because they cause model produce a “forgetting” property “memory”...
Oxide-based memristors by incorporating thermally enhanced layer (TEL) have showed great potential in electronic devices for high-efficient and high-density neuromorphic computing owing to the improvement of multilevel resistive switching. However, research on mechanism switching regulation is still lacking. In this work, based method finite element numerical simulation analysis, a bilayer oxide-based memristor Pt/HfO2(5 nm)/Ta2O5(5 nm)/Pt with Ta2O5TEL was proposed. The oxygen vacancy...
Abstract In-memory computing electronic components offer a promising non-von Neumann strategy to develop energy-efficient and high-speed hardware systems for artificial intelligence (AI). However, the implementation of conventional demands huge computational power budget, thereby limiting their wider application. In this work, we propose novel superconducting in-memory architecture by coupling memristor device. Leveraging phase transition superconductor induced external applied Joule power,...
In this study, a NbO2-based selector was designed that can change high resistance states to low due the insulator–metal transition (IMT). A one-selector-one-resistor cell for 3D crossbar array composed of and TiN/TiO2/TiN bipolar resistive random access memory (RRAM) in series modeled using COMSOL finite element multiphysics software package. First, temperature dependencies electrical conductivity (σ), thermal (kth), mass specific heat (CP) were used compare two IMT selectors, which showed...
An ITO/PMMA/SiC-NWs/ITO device enables visual adaptation in vision systems. Integrated with an LIF circuit, it reflects via frequency changes. In extreme weather, this system accuracy reached 97%, 12% higher than traditional
Abstract Statistical postprocessing is commonly applied to reduce location and dispersion errors of probabilistic forecasts provided by numerical weather prediction (NWP) models. If postprocessed forecast scenarios are required, the combination ensemble model output statistics (EMOS) for univariate with copula coupling (ECC) or Schaake shuffle (ScS) retain dependence structure raw a state-of-the-art approach. However, modern machine learning methods may lead both better skill more realistic...
Herein, an improved memristor model with a controllable forgetting rate due to ion diffusion is proposed. A synaptic learning circuit based on this simulated PSpice complete bionics. First, the pulse pair superposition method, which consistent biological phenomena, used verify spike timing‐dependent plasticity (STDP); proves that modified simulates behavior. Second, habituation constructed from and analog behavioral modeling (ABM) device designed realize nonassociative learning. Finally, new...
Abstract In this work, a compact model of the diffusive memristor is proposed from perspective transition electronic transmission mechanisms induced by dynamics filament. First, new physical established based on tunneling that are used to fit experimental data, and results indicate it versatile enough for various memristors. addition, threshold voltage ( V th ) negatively correlates with ratio ionic migration diffusion coefficient u i /Ds ), hold h positively Ds/u which useful selection...
A memristor‐based reinforcement learning (RL) system has shown outstanding performance in achieving efficient autonomous decision‐making and edge computing. Sarsa ( λ ) is a classical multistep RL algorithm that records state with decay guides policy updates, significantly improving the convergence speed. However, implementation of traditional computing hardware confined by extensive computation power exponential decay. Herein, value update equation for implemented using topological...
The analog neural network to spiking (ANN-to-SNN) conversion is an effective method for improving the performance of SNNs. However, existing mainstream (rectified linear unit, ReLU) still face problem weak ability adversarial attacks. In this brief, inspired by radial basis function and "near enhancement far inhibition (NEFI)" properties biological neurons, a threshold switching (TS) memristor based neuron (RBSN) circuit proposed ANN-to-SNN implementation. results indicate that RBSN can...
Six different interfaces namely, armchair Graphene (aGNR), zigzag (zGNR), and surface defect (zGNR1) nanoribbons with uni- bi-laminar <001>-oriented NiO were studied. First, the Mulliken mean difference populations, interface energy, adhesion energy calculated by Cambridge sequential total package (CASTEP). The aGNR/NiO showed higher population as compared to other structures (i.e., was more compact than rest of interfaces). Moreover, lowest values along negligible aberration...
A 2-D semi-analytical model of double gate (DG) tunneling field-effect transistor (TFET) is proposed. By aid introducing two rectangular sources located in the dielectric layer and channel, Poisson equation solved by using a method combined with an eigenfunction expansion method. The expression surface potential obtained, which special function for infinite series expressions. influence mobile charges on profile taken into account proposed model. On basis profile, shortest length average...