Results 71 to 80 of about 9,355 (180)

Activation‐Integrated and Memory‐Assisted Dynamic‐Latch Quantizer for Variation‐Tolerant and Low‐Energy Neuromorphic Computing

Advanced Intelligent Systems, EarlyView.
A memory‐assisted dynamic‐latch ADC integrating charge‐trap flash enables ultra‐low‐energy quantization and in‐ADC nonlinear activation for variation‐tolerant neuromorphic computing. Analog‐to‐digital converters (ADCs) remain the dominant area/energy bottleneck in neuromorphic computing (NC) systems.
Jonghyun Ko, Jiseong Im, Ryun‐Han Koo, Sung‐Ho Park, Jong‐Ho Lee   +4 more
wiley   +1 more source

Demonstration of transfer learning using 14 nm technology analog ReRAM array

Frontiers in Electronics
Analog memory presents a promising solution in the face of the growing demand for energy-efficient artificial intelligence (AI) at the edge. In this study, we demonstrate efficient deep neural network transfer learning utilizing hardware and algorithm co-
Fabia Farlin Athena, Omobayode Fagbohungbe, Nanbo Gong, Malte J. Rasch, Jimmy Penaloza, SoonCheon Seo, Arthur Gasasira, Paul Solomon, Valeria Bragaglia, Steven Consiglio, Hisashi Higuchi, Chanro Park, Kevin Brew, Paul Jamison, Christopher Catano, Iqbal Saraf, Claire Silvestre, Xuefeng Liu, Babar Khan, Nikhil Jain, Steven McDermott, Rick Johnson, I. Estrada-Raygoza, Juntao Li, Tayfun Gokmen, Ning Li, Ruturaj Pujari, Fabio Carta, Hiroyuki Miyazoe, Martin M. Frank, Antonio La Porta, Devi Koty, Qingyun Yang, Robert D. Clark, Kandabara Tapily, Cory Wajda, Aelan Mosden, Jeff Shearer, Andrew Metz, Sean Teehan, Nicole Saulnier, Bert Offrein, Takaaki Tsunomura, Gert Leusink, Vijay Narayanan, Takashi Ando   +45 more
doaj   +1 more source

Lead‐free inorganic halide perovskite‐based synaptic memory for next generation neuromorphic computing

InfoMat, EarlyView.
Lead‐free inorganic halide perovskites enable resistive switching synaptic devices capable of mimicking biological learning and multimodal information processing, offering a promising platform for next‐generation neuromorphic computing and artificial intelligence hardware. Abstract Inorganic halide perovskites (IHPs) have emerged as promising materials
Subhasish Chanda, Deepak Kumar, Iman Biswas, Manisha Sharma, Youngmin Lee, Sejoon Lee, Sanjeev Kumar Sharma, Aniruddha Mondal   +7 more
wiley   +1 more source

Memory effects in complex materials and nanoscale systems

, 2010
Memory effects are ubiquitous in nature and are particularly relevant at the nanoscale where the dynamical properties of electrons and ions strongly depend on the history of the system, at least within certain time scales.
Di Ventra, Massimiliano, Pershin, Yuriy V.   +1 more
core   +1 more source

Opportunities for 2D‐Material‐Based Multifunctional Devices and Systems in Bioinspired Neural Networks

Small, EarlyView.
Bio‐inspired computing offers a route to highly energy‐efficient artificial intelligence. The unique physical properties of two‐dimensional (2D) materials can further enhance such computing approaches. This perspective highlights recent developments in 2D materials‐based neuromorphic devices and discusses future opportunities for integrating such novel
Jin Feng Leong, Maheswari Sivan, Jieming Pan, Zihang Fang, Jianan Li, Zefeng Xu, Shi Zhao, Quanzhen Wan, Evgeny Zamburg, Aaron Voon‐Yew Thean   +9 more
wiley   +1 more source

Honey-ReRAM Enabled Sustainable Edge AI System for IoT Applications

IEEE Access
This paper is toward a promising solution to address the environmental sustainability challenge in computing by building brain-inspired and green non-Von Neumann systems with Resistive Random-Access Memory (ReRAM) made from natural organic materials ...
Jinhui Wang, Feng Zhao, Mohammad Rafeeq Khan, Md. Mehedi Hasan Tanim, Zoe Templin, Harshvardhan Uppaluru   +5 more
doaj   +1 more source

The nature of column boundaries in micro-structured silicon oxide nanolayers

APL Materials, 2021
Columnar microstructures are critical for obtaining good resistance switching properties in SiOx resistive random access memory (ReRAM) devices. In this work, the formation and structure of columnar boundaries are studied in sputtered SiOx layers.
K. Patel, J. Cottom, A. Mehonic, W. H. Ng, A. J. Kenyon, M. Bosman, A. L. Shluger   +6 more
doaj   +1 more source

Training and Operation of an Integrated Neuromorphic Network Based on Metal-Oxide Memristors

, 2014
Despite all the progress of semiconductor integrated circuit technology, the extreme complexity of the human cerebral cortex makes the hardware implementation of neuromorphic networks with a comparable number of devices exceptionally challenging.
Adam, Gina, Hoskins, Brian, Likharev, Konstantin K., Merrikh-Bayat, Farnood, Prezioso, Mirko, Strukov, Dmitri B.   +5 more
core   +1 more source

Photo‐Induced Phase Segregation in Mixed Halide Perovskite Structures and Various Methods of Suppression

Advanced Materials Interfaces, Volume 13, Issue 6, 16 March 2026.
Mixed halide perovskites suffer from photo‐induced phase segregation, leading to compositional instability and degraded device performance. This review summarizes the dynamic behavior and kinetics of phase segregation in thin films under external stimuli, analyzes compositional and environmental effects, and proposes suppression strategies to enhance ...
Yong Hyun Kim, Hyojung Kim
wiley   +1 more source

A Relaxed Quantization Training Method for Hardware Limitations of Resistive Random Access Memory (ReRAM)-Based Computing-in-Memory

IEEE Journal on Exploratory Solid-State Computational Devices and Circuits, 2020
Nonvolatile computing-in-memory (nvCIM) exhibits high potential for neuromorphic computing involving massive parallel computations and for achieving high energy efficiency.
Wei-Chen Wei, Chuan-Jia Jhang, Yi-Ren Chen, Cheng-Xin Xue, Syuan-Hao Sie, Jye-Luen Lee, Hao-Wen Kuo, Chih-Cheng Lu, Meng-Fan Chang, Kea-Tiong Tang   +9 more
doaj   +1 more source