Zobrazeno 1 - 10
of 9 094
pro vyhledávání: '"Resistive random-access memory"'
Publikováno v:
Electronic Materials, Vol 5, Iss 2, Pp 71-79 (2024)
In this study, the bipolar switching behaviors in ZnO/HfO2 bilayer resistive random-access memory (RRAM), depending on different metal top electrodes (TE), are analyzed. For this purpose, devices with two types of TE–TiN/Ti and Pd, which have varyi
Externí odkaz:
https://doaj.org/article/7f1d2e2702db47329b8c91f4fd01f394
Autor:
Danian Dong, Woyu Zhang, Yuanlu Xie, Jinshan Yue, Kuan Ren, Hongjian Huang, Xu Zheng, Wen Xuan Sun, Jin Ru Lai, Shaoyang Fan, Hongzhou Wang, Zhaoan Yu, Zhihong Yao, Xiaoxin Xu, Dashan Shang, Ming Liu
Publikováno v:
Advanced Intelligent Systems, Vol 6, Iss 10, Pp n/a-n/a (2024)
Reservoir computing (RC) possesses a simple architecture and high energy efficiency for time‐series data analysis through machine learning algorithms. To date, RC has evolved into several innovative variants. The next generation reservoir computing
Externí odkaz:
https://doaj.org/article/ccf274fc05ba4f94bfb4dcb1dd3a1470
Autor:
Furqan Zahoor, Ramzi A. Jaber, Usman Bature Isyaku, Trapti Sharma, Faisal Bashir, Haider Abbas, Ali S. Alzahrani, Shagun Gupta, Mehwish Hanif
Publikováno v:
Results in Engineering, Vol 23, Iss , Pp 102761- (2024)
In the electronics industry, binary devices have played a critical role since the development of solid-state transistors. While binary technology associates devices' inherent ability to be either ON or OFF with two logic levels, it offers the least a
Externí odkaz:
https://doaj.org/article/f4b595bd6d154ccca823827e283dffc1
Autor:
Tangyou Sun, Fantao Yu, Xiaosheng Tang, Haiou Li, Fabi Zhang, Zhimou Xu, Qing Liao, Zhiqiang Yu, Xingpeng Liu, Peihua Wangyang, Hezhang Li, Ying Peng
Publikováno v:
Journal of Materiomics, Vol 10, Iss 2, Pp 440-447 (2024)
The field of artificial intelligence and neural computing has been rapidly expanding due to the implementation of resistive random-access memory (RRAM) based artificial synaptic. However, the low flexibility of conventional RRAM materials hinders the
Externí odkaz:
https://doaj.org/article/a353117c07e04009920d5a9add2552fb
Autor:
Woyu Zhang, Zhi Li, Xinyuan Zhang, Fei Wang, Shaocong Wang, Ning Lin, Yi Li, Jun Wang, Jinshan Yue, Chunmeng Dou, Xiaoxin Xu, Zhongrui Wang, Dashan Shang
Publikováno v:
Advanced Intelligent Systems, Vol 6, Iss 7, Pp n/a-n/a (2024)
Artificial intelligence for graph‐structured data has achieved remarkable success in applications such as recommendation systems, social networks, drug discovery, and circuit annotation. Graph convolutional networks (GCNs) are an effective way to l
Externí odkaz:
https://doaj.org/article/b30619a65a6d4e07b5d70d9ead20fd49
Autor:
Yen‐Jung Chen, Hung‐Yang Lo, Chun‐Chien Chiu, Che‐Hung Wang, Jan‐Chi Yang, Jui‐Yuan Chen, Wen‐Wei Wu
Publikováno v:
Small Structures, Vol 5, Iss 7, Pp n/a-n/a (2024)
Resistive random‐access memory (RRAM) is considered the next‐generation nonvolatile memory owing to its simplicity, low power consumption, and high storage density. Resistive switching (RS) occurs in a wide range of materials among the transition
Externí odkaz:
https://doaj.org/article/5f1656e6165642179c6eee4a43c42d48
Publikováno v:
Chip, Vol 3, Iss 2, Pp 100086- (2024)
As a typical representative of nanomaterials, carbon nanomaterials have attracted widespread attention in the construction of electronic devices owing to their unique physical and chemical properties, multi-dimensionality, multi-hybridization methods
Externí odkaz:
https://doaj.org/article/cc46399afcaf4c019b7908173c8502ef
Autor:
Mahmoud Darwish, László Pohl
Publikováno v:
Electronic Materials, Vol 5, Iss 1, Pp 17-29 (2024)
This article investigates resistive random access memory (ReRAM) crossbar memory arrays, which is a notable development in non-volatile memory technology. We highlight ReRAM’s competitive edge over NAND, NOR Flash, and phase-change memory (PCM), pa
Externí odkaz:
https://doaj.org/article/7889742e9f2c4bb9a0aaddd790fe66c8
Publikováno v:
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol 10, Pp 31-39 (2024)
Memory-augmented neural networks (MANNs) require large external memories to enable long-term memory storage and retrieval. Content-addressable memory (CAM) is a type of memory used for high-speed searching applications and is well-suited for MANNs. R
Externí odkaz:
https://doaj.org/article/5ea8eca713e4442597a3ac1a5272f083
Autor:
Saion K. Roy, Naresh R. Shanbhag
Publikováno v:
IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, Vol 10, Pp 22-30 (2024)
Resistive in-memory computing (IMC) architectures currently lag behind SRAM IMCs and digital accelerators in both energy efficiency and compute density due to their low compute accuracy. This article proposes the use of signal-to-noise-plus-distortio
Externí odkaz:
https://doaj.org/article/28107b97e2f8428e821dcc1d60abbe85