Results 101 to 110 of about 394,763 (294)

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

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source

Monolithic 3D‐Integrated All‐Solid Ion‐Gated Carbon Nanotube Transistors With Tunable Ionic Conductance for Multi‐Timescale Reservoir Computing

Advanced Materials, EarlyView.
A dual‐timescale reservoir based on monolithically 3D (M3D)‐integrated CNT solid ion‐gated transistors is demonstrated. Tunable ionic dynamics and pulse‐engineered operation enable linear and symmetric synaptic updates. The M3D‐integrated array achieves robust temporal encoding and accurate classification of moving MNIST sequences, highlighting its ...
Haksoon Jung, Hanbin Cho, Yongwoo Lee, Seunghun Baek, Hyeongjun Kim, Yun Goo Ro, Hyunhyub Ko, Joonki Suh, Yong‐Young Noh, Jimin Kwon   +9 more
wiley   +1 more source

Optoelectronic Nanofluidic Neural Networks for Ionic Computing

Advanced Materials, EarlyView.
An ion‐based optoelectronic nanofluidic memristor enables neuromorphic computing in aqueous environments. With tunable ionic memory and multimodal synaptic plasticity, it realizes densely connected ionic neural networks capable of image classification, motion prediction, logic computation, and real‐time in‐sensor computing, advancing fully connected ...
Yaxin Huang, Zhiyuan Du, Changjin Wu, Binglin Zeng, Yingnan Cao, Mingliang Li, Liren Zhang, Qingxin Guo, Chao Huang, Can Li, Jinyao Tang   +10 more
wiley   +1 more source

Photoactive Tweezers

Advanced Materials, EarlyView.
A photoactive tweezers system based on photoactive colloids is developed and systematically investigated in this study. Through experimental and theoretical methods, we demonstrate that the photoredox reaction catalyzed by a dye‐sensitized TiO2 particle generates a strong positive phototaxis, enabling self‐entrapment in the beam center.
Jingyuan Chen, Qingxin Guo, Shiwei Zhang, Donghao Cui, Changjin Wu, Pei Xu, Wei Wang, Kai Lou, Binglin Zeng, Jinyao Tang   +9 more
wiley   +1 more source

Special Issue Dedicated to the 16th International Symposium on Parameterized and Exact Computation. [PDF]

Algorithmica, 2022
Golovach PA, Zehavi M.
europepmc   +1 more source

Multiscale kernels

Advances in Computational Mathematics, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Noise‐Tunable Memristor Enabling Programmable Probabilistic Neurons for Frequency‐Selective Time‐Series Signal Encoding

Advanced Materials, EarlyView.
Memristors offer tunable resistance and intrinsic instability, making them promising tunable noise sources. We propose a spiking‐rate‐programmable probabilistic neuron using a Ru/TaOx/Pt memristor, where resistance‐dependent noise enables frequency‐selective encoding.
Do Hoon Kim, Seoeun Jang, Hakseung Rhee, Min Gu Lee, Daehee Kim, Taewook Go, Woon Hyung Cheong, Hanchan Song, Kyung Min Kim   +8 more
wiley   +1 more source

Propagation Kernels

CoRR, 2014
We introduce propagation kernels, a general graph-kernel framework for efficiently measuring the similarity of structured data. Propagation kernels are based on monitoring how information spreads through a set of given graphs. They leverage early-stage distributions from propagation schemes such as random walks to capture structural information encoded
Marion Neumann, Roman Garnett, Christian Bauckhage, Kristian Kersting   +3 more
openaire   +2 more sources

Analog Tensor Processing With Carbon Nanotube In‐Memory Matrix Multiplications for Edge Computer Vision Acceleration

Advanced Materials, EarlyView.
This work prototypes a carbon nanotube‐based analog tensor core that performs in‐memory, parallel visual processing. Integrating non‐volatile memories and compact circuits, the core enables high‐speed analog matrix multiplications and can demonstrate accurate three dimensional (3D) spatial transformation and edge detection. With lightweight design, the
Jingfang Pei, Lekai Song, Songwei Liu, Yingyi Wen, Yaoqiang Zhou, Yang Liu, Pengyu Liu, Wenyu Cui, Xin Lu, Teng Ma, Zegao Wang, Guohua Hu   +11 more
wiley   +1 more source