Results 41 to 50 of about 3,700 (260)

Thermally Pre‐Formed Reconfigurable Resistive Random‐Access Memory Crossbar Arrays: A Dual‐Mode Platform for Robust Physically Unclonable Functions and In‐Memory Computing

Advanced Functional Materials, EarlyView.
A reconfigurable RRAM platform utilizing thermally pre‐formed filaments (TPFs) is developed to realize robust hardware security. By exploiting the thermodynamic stochasticity of TPFs, exceptionally reliable physically unclonable functions (PUFs) are achieved.
Seongbin Kwon, Taewon Lee, Dohyeong Kim, Sungmin Hwang, Sungjoon Kim   +4 more
wiley   +1 more source

Identification and classification of objects in images obtained by UAV and orbital base imaging equipmenttion

Системный анализ и прикладная информатика, 2023
To identify and classify objects on images obtained using UAV imaging and orbital-based imaging, a neural network classification model based on the use of an autoencoder and built on the architecture of an ensemble of multilayer perceptrons is proposed ...
A. A. Doudkin, V. V. Ganchenko, A. V. Inyutin, E. E. Marushko   +3 more
doaj   +1 more source

Multilayer Perceptron Algebra

CoRR, 2017
Artificial Neural Networks(ANN) has been phenomenally successful on various pattern recognition tasks. However, the design of neural networks rely heavily on the experience and intuitions of individual developers. In this article, the author introduces a mathematical structure called MLP algebra on the set of all Multilayer Perceptron Neural Networks ...
openaire   +2 more sources

Room‐Temperature Skyrmionic Synapse in 2D Ferromagnet Fe3GaTe2 Operating via Collective Spin Texture Transformation

Advanced Materials, EarlyView.
We demonstrate a neuromorphic synapse in 2D Fe3GaTe2 flakes. The device operates via a current‐driven transformation from a skyrmion‐lattice to a stripe‐domain state, yielding a linear anomalous Hall resistance response with a tunable slope to enable multiply‐accumulate operations. Simulations confirm its viability in artificial neural networks.
Jixiang Huang, Tongji Zhu, PeiYu Cai, Xiaoming Ma, Zhen Wang, Ruifu Zhang, Yi Hao, Jingdi Lu, Liubing He, Jun Xu, Yuejie Zhang, Wanjun Jiang, Jing Tao, Shiming Lei, Pavel Parchinskiy, Jing Teng, Lingfei Wang, Wei Niu, Elton J.G. Santos, Xiaoqian Zhang, Peng Li   +20 more
wiley   +1 more source

Meta-Heuristic Optimization Methods for Quaternion-Valued Neural Networks

Mathematics, 2021
In recent years, real-valued neural networks have demonstrated promising, and often striking, results across a broad range of domains. This has driven a surge of applications utilizing high-dimensional datasets.
Jeremiah Bill, Lance Champagne, Bruce Cox, Trevor Bihl   +3 more
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

SS-MLP: A Novel Spectral-Spatial MLP Architecture for Hyperspectral Image Classification

Remote Sensing, 2021
Convolutional neural networks (CNNs) are the go-to model for hyperspectral image (HSI) classification because of the excellent locally contextual modeling ability that is beneficial to spatial and spectral feature extraction. However, CNNs with a limited
Zhe Meng, Feng Zhao, Miaomiao Liang
doaj   +1 more source

Path‐Decoupled Cation‐Eutaxy III–V van der Waals Memristive Semiconductors for Mitigating the Neuromorphic Accuracy‐Energy Trade‐off

Advanced Materials, EarlyView.
Path‐decoupled III–V van der Waals memtransistors spatially separate ionic and electronic transport to overcome the conventional trade‐off between accuracy and energy in neuromorphic hardware. Mobile K+ ions in the vdW gaps set a wide conductance window, Gmax/Gmin, while gate‐tunable hole conduction lowers programming energy, enabling reliable ...
Jihong Bae, Ji Hoon Han, Taeyoung Kim, Jongbum Won, Seokmin Park, Gyu Won Kim, Sungsoon Kim, Hong Choi, Taehoon Kim, Hong‐Sub Lee, Jae‐Hyun Lee, Young Jin Choi, Jinwoo Cheon, Wooyoung Shim   +13 more
wiley   +1 more source

Depth Classification of Defects Based on Neural Architecture Search

IEEE Access, 2021
As an important part of non-destructive testing, infrared thermography testing is widely used in various fields of industrial development for monitoring the quality of metal parts. Considering the problem of low detection rate of surface defects on steel
Haoze Chen, Zhijie Zhang, Chenyang Zhao, Jiaqi Liu, Wuliang Yin, Yanfeng Li, Fengxiang Wang, Chao Li, Zhenyu Lin   +8 more
doaj   +1 more source

Machine Learning Accelerated Computational Design of Bio‐Inspired Catalysts in the Nitrogen Reduction Reaction

Advanced Materials, EarlyView.
We introduce a computational workflow that combines quantum chemical calculations and machine learning techniques to predict the catalytic performance of a wide range of catalysts in the nitrogen reduction reaction (NRR). The analysis of the trained models provides insights into the complex structure–activity relationship in experimental catalytic ...
Leonardo Di Ciano, Zihan You, Haoran Chen, Qifan Zhong, Rong‐Zhen Liao, Shaoqi Zhan   +5 more
wiley   +1 more source