Results 101 to 110 of about 7,604,757 (293)

Memristive‐Gated RC‐Delay Synaptic Transistors for Time‐Encoded Analog in‐Memory Computing

Advanced Functional Materials, EarlyView.
A Memristive‐Gated Transistor for Time‐Encoded Analog In‐Memory Computing — By exploiting the RC delay of a self‐rectifying interface‐type memristor, nonlinear I–V distortion is structurally bypassed, enabling 3‐bit nonvolatile memory, spike‐timing‐based analog encoding, and hardware‐calibrated reservoir‐computing validation within a unified device ...
Yun‐Seo Shin, Eunjoo Yoo, Ki‐Hoon Son, Hyun‐Sik Kim, Dae‐Hee Han, Jeong Hyeon Son, Seung Hwan Lee, Hong‐Sub Lee   +7 more
wiley   +1 more source

Ultra-compact multi-task processor based on in-memory optical computing

Light: Science & Applications
To enhance the computational density and energy efficiency of on-chip neuromorphic hardware, this study introduces a novel network architecture for multi-task processing with in-memory optical computing. On-chip optical neural networks are celebrated for
Wencan Liu, Yuyao Huang, Run Sun, Tingzhao Fu, Sigang Yang, Hongwei Chen   +5 more
doaj   +1 more source

A Neural Network Computational Spectrometer Trained by a Small Dataset with High-Correlation Optical Filters

Sensors
A computational spectrometer is a novel form of spectrometer powerful for portable in situ applications. In the encoding part of the computational spectrometer, filters with highly non-correlated properties are requisite for compressed sensing, which ...
Haojie Liao, Lin Yang, Yuanhao Zheng, Yansong Wang   +3 more
doaj   +1 more source

Human emotion recognition with a microcomb-enabled integrated optical neural network. [PDF]

Nanophotonics, 2023
Cheng J, Xie Y, Liu Y, Song J, Liu X, He Z, Zhang W, Han X, Zhou H, Zhou K, Zhou H, Dong J, Zhang X.   +12 more
europepmc   +1 more source

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

Advanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan, Hocheon Yoo, Benoît H. Lessard, Ioannis Kymissis, Chang‐Hyun Kim   +4 more
wiley   +1 more source

Correlated optical convolutional neural network with “quantum speedup”

Light: Science & Applications
Compared with electrical neural networks, optical neural networks (ONNs) have the potentials to break the limit of the bandwidth and reduce the consumption of energy, and therefore draw much attention in recent years.
Yifan Sun, Qian Li, Ling-Jun Kong, Xiangdong Zhang   +3 more
doaj   +1 more source

Generative Adversarial Optical Networks Using Diffractive Layers for Digit and Action Generation

Photonics
Within the traditional electronic neural network framework, Generative Adversarial Networks (GANs) have achieved extensive applications across multiple domains, including image synthesis, style transfer and data augmentation.
Pei Hu, Tengyu Cui, Yuanyuan Zhang, Shuai Feng   +3 more
doaj   +1 more source

Optical neural network via loose neuron array and functional learning. [PDF]

Nat Commun, 2023
Huo Y, Bao H, Peng Y, Gao C, Hua W, Yang Q, Li H, Wang R, Yoon SE.   +8 more
europepmc   +1 more source

On-Chip Optical Convolutional Neural Networks

CoRR, 2018
Convolutional Neural Networks (CNNs) are a class of Artificial Neural Networks(ANNs) that employ the method of convolving input images with filter-kernels for object recognition and classification purposes. In this paper, we propose a photonics circuit architecture which could consume a fraction of energy per inference compared with state of the art ...
Hengameh Bagherian, Scott A. Skirlo, Yichen Shen 0001, Huaiyu Meng, Vladimir Ceperic, Marin Soljacic   +5 more
openaire   +2 more sources

Bio‐Inspired Artificial Ionic Mechanoreceptor

Advanced Functional Materials, EarlyView.
A skin‐inspired artificial mechanoreceptor based on ionic interactions is presented for biomimetic tactile sensing. Pressure‐driven ionic redistribution within microfluidic channels generates a self‐powered electrical signal without external bias. The generated waveform exhibits mechanoreceptor‐like temporal features, including overshoot and undershoot,
Mohammad Akbari, Jeppe Don, Lasse A. N. Pedersen, John Noee, Rassoul Tabassian   +4 more
wiley   +1 more source