A5109953585- Face and Expression Recognition
- Advanced Memory and Neural Computing
- Ferroelectric and Negative Capacitance Devices
- Advanced Clustering Algorithms Research
- Neural Networks and Applications
- Semiconductor materials and devices
- Graphene research and applications
- Advancements in Semiconductor Devices and Circuit Design
- Remote-Sensing Image Classification
- Machine Learning and Data Classification
- Carbon Nanotubes in Composites
- Industrial Vision Systems and Defect Detection
- Electronic and Structural Properties of Oxides
- Text and Document Classification Technologies
- Radiation Effects in Electronics
- Imbalanced Data Classification Techniques
- Image Retrieval and Classification Techniques
- Image and Signal Denoising Methods
- Fault Detection and Control Systems
- Anomaly Detection Techniques and Applications
- Neuroscience and Neural Engineering
- Spectroscopy and Chemometric Analyses
- Gold and Silver Nanoparticles Synthesis and Applications
- Nanomaterials for catalytic reactions
- Diamond and Carbon-based Materials Research
Jimei University
2015-2024
University of Groningen
2024
Xi'an Jiaotong University
2008-2024
National Natural Science Foundation of China
2023
Sun Yat-sen University
2022
IBM (United States)
2006
Advanced Micro Devices (United States)
2006
Resistive Random Access Memory (RRAM) is considered one of the most promising candidates for big data storage. By using atomic layer deposition and magnetron sputtering, HfO2 thin films were prepared on ITO first, which exhibited good resistive switching (RS) characteristics in structure Ag/HfO2/ITO. analyzing RS mechanism, it found that both metal conductive filaments oxygen vacancy coexisted Sn ion can influence retention RRAM. Furthermore, a device Ag/HfO2/Pt was proposed prepared,...
Robust principal component analysis (RPCA) is a technique that aims to make (PCA) robust noise samples. The current modeling approaches of RPCA were proposed by analyzing the prior distribution reconstruction error terms. However, these methods ignore influence samples with large errors, as well valid information in space, which will degrade ability PCA extract data. In order solve this problem, Fuzzy sparse deviation regularized Analysis (FSD-PCA) paper. First, FSD-PCA learns components...
Principal component analysis (PCA) is one of the most versatile techniques for unsupervised dimension reduction, which implemented as a fundamental preprocessing method in multiple tasks statistics and machine learning research because its efficiency. Nevertheless, researchers have concentrated on identification outliers that do not conform to low-dimensional approximation through statistical methods, e.g., outlier rejection, without giving insights each data point with dynamic ratio...
Cu 2 O is a direct and narrow band-gap material; hence, it serves as an important candidate material for applications such solar cells.In this study, copper (Cu) metal was used target the reactive sputtering method to deposit cuprous oxide (Cu O) cupric (CuO) thin films on indium tin (ITO) glass.The formation of CuO controlled by varying oxidation conditions, controlling deposition atmosphere (called ratio).The microstructure, crystalline orientation, optical properties were measured using...
Principal Component Analysis (PCA) aims to acquire the principal component space containing essential structure of data, instead being used for mining and extracting data. In other words, contains not only information related data but also some unrelated information. This frequently occurs when intrinsic dimensionality is unknown or it has complex distribution characteristics such as multi-modalities, manifolds, etc. Therefore, unreasonable identify noise useful based solely on...
Feature selection serves as a fundamental technique in machine learning and data analysis, playing crucial role extracting valuable features from large-scale high-dimensional datasets that may contain irrelevant features. To enhance the performance of feature selection, regularizers like <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\ell _{1}}$</tex-math></inline-formula> -norm or...
AdaBoost is a method to improve given learning algorithm's classification accuracy by combining its hypotheses. Adaptivity, one of the significant advantages AdaBoost, makes maximize smallest margin so that has good generalization ability. However, when samples with large negative margins are noisy or atypical, maximized actually "hard margin." The adaptive feature sensitive sampling fluctuations, and prone overfitting. Therefore, traditional schemes prevent from overfitting heavily damping...
This paper investigates the effect of total dose radiation on electrostatic potential distribution and related short-channel effects (SCEs) silicon-on-insulator (SOI) metal-oxide-semiconductor (MOS) devices with a vertical Gaussian doping profile. A new approximation 2-D function perpendicular to channel for fully depleted SOI MOS field-effect transistors (FETs) is applied in analytical threshold voltage model derivation. The impact interface traps oxide-trapped charge profile, scaling, SCEs...
Resistive random access memory (RRAM) has emerged as a competitive candidate for nonvolatile due to its high speed, low power consumption, simple structure, strong scalability, and CMOS compatibility. Herein, an overview of the electrodes resistive layers is first discussed according material properties structure RRAM. Then, recent advances in mechanisms RRAM are comprehensively evaluated based on experimental research results fundamental physics principles. electrochemical metallization...
Resistive random access memory (RRAM) has emerged as a technology due to its simple structure and compatibility with CMOS technology. In recent years, it was reported that HfO2-based RRAMs are promising for commercial applications but suffer from relatively poor performance in stability retention the formation breakage of conductive channels. this work, we introduced layer Ag nanoparticles embedded HfO2 resistive switching address randomness RRAMs. It found embedding enhances local electric...