Neuromorphic Computing DOI

Devendra G. Pandey,

Yogesh Kumar Sharma, Nimish Kumar

и другие.

Advances in computational intelligence and robotics book series, Год журнала: 2024, Номер unknown, С. 411 - 428

Опубликована: Окт. 4, 2024

The exponential growth of data and information has stimulated technological progress in computing systems that utilize them to effectively discover patterns produce important insights. Neural network algorithms have been applied conventional silicon transistor-based hardware do highly parallel computations, drawing inspiration from the structure functions biological synapses neurons brain. Nevertheless, composed many transistors are limited storing binary data, utilization intricate neuron circuits handle these digital states poses challenges achieving low-power low-latency computing. This study examines significance developing memories switches for synaptic neural components building Neuromorphic can efficiently conduct cognitive tasks recognition. chapter closely rates latest computing, focusing on how changes impact edge Internet Things technologies. It is also being thought about use tiny short-term memory copy action neurons. Once this done, more Studies areas should be able focus design, circuitry, devices systems.

Язык: Английский

Integrated Photonic Neural Networks for Equalizing Optical Communication Signals: A Review DOI Creative Commons
Luís C. B. Silva, Pablo Rafael Neves Marciano, Maria Pontes

и другие.

Photonics, Год журнала: 2025, Номер 12(1), С. 39 - 39

Опубликована: Янв. 4, 2025

The demand for high-capacity communication systems has grown exponentially in recent decades, constituting a technological field constant change. Data transmission at high rates, reaching tens of Gb/s, and over distances that can reach hundreds kilometers, still faces barriers to improvement, such as distortions the transmitted signals. Such include chromatic dispersion, which causes broadening pulse. Therefore, development solutions adequate recovery signals distorted by complex dynamics channel currently constitutes an open problem since, despite existence well-known efficient equalization techniques, these have limitations terms processing time, hardware complexity, especially energy consumption. In this scenario, paper discusses emergence photonic neural networks promising alternative equalizing optical Thus, review focuses on applications, challenges, opportunities implementing integrated scenario signal equalization. main work carried out, ongoing investigations, possibilities new research directions are also addressed. From review, it be concluded perceptron perform slightly better greater than reservoir computing networks, but with lower data rates. It is important emphasize photonics been growing years, so beyond scope address all existing applications networks.

Язык: Английский

Процитировано

2

Recent advances in fluidic neuromorphic computing DOI Creative Commons
Cheryl Suwen Law, Juan Wang, Kornelius Nielsch

и другие.

Applied Physics Reviews, Год журнала: 2025, Номер 12(2)

Опубликована: Апрель 21, 2025

Human brain is capable of optimizing information flow and processing without energy-intensive data shuttling between processor memory. At the core this unique capability are billions neurons connected through trillions synapses—basic units brain. The action potentials or “spikes” based temporal using regulated ions across ion channels in neuron cells allows sparse efficient transmission Emerging systems on confined fluidic have provided a framework for new type neuromorphic computing with lower energy consumption, hardware-level plasticity, multiple carriers that emulate natural processes mechanisms human These mimic neuronal architectures by harnessing modulating transport along artificial channels. spikes-induced ion-to-surface interactions within these enables control ionic conductivity to achieve synaptic plasticity realization brain-inspired functionalities such as memory effect signal transmission. Herein, review provides an overview recent advances devices memristors other components, covering their basic operations, materials architectures, well applications computing. concludes brief outline challenges emerging technologies face outlook development fluidic-based

Язык: Английский

Процитировано

1

Advancing Civil Engineering: The Transformative Impact of Neuromorphic Computing on Infrastructure Resilience and Sustainability DOI Creative Commons
Ali Akbar Firoozi, Ali Asghar Firoozi,

Yasser Alashker

и другие.

Results in Engineering, Год журнала: 2024, Номер unknown, С. 103487 - 103487

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

3

Advanced Materials Research at CUHK: From Biomedicine to Electronics and Beyond DOI
Chuanbin Mao

Advanced Materials, Год журнала: 2025, Номер 37(2)

Опубликована: Янв. 1, 2025

This special issue spans a diverse array of topics, including nanomedicine, tissue engineering, regenerative medicine, organs-on-chips, biosensing, soft robotics, smart devices, nanofabrication, energy saving and storage, catalysis, spintronics, electronics, neuromorphic computing. It showcases the breadth depth advanced materials research at Chinese University Hong Kong (CUHK), highlighting innovation, collaboration, excellence CUHK's scientists.

Язык: Английский

Процитировано

0

Reimagining Robots: The Future of Cybernetic Organisms with Energy-Efficient Designs DOI
Stefan Stavrev

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Effect of 60Co γ‐Ray Irradiation on the Linearity of Conductance Updating of the HfOx:Mg(9%)‐Based Memristive Synapses Studied by Electrochemical Impedance Spectroscopy DOI

H. H. Feng,

Hongjia Song,

Linyan Yao

и другие.

physica status solidi (a), Год журнала: 2025, Номер unknown

Опубликована: Апрель 9, 2025

Binary metal oxide memristive synapses, with their simple structure, high integration density, low power, and speed, are promising for aerospace computing chips. However, irradiation can degrade performance. This article investigates the effect of 60 Co γ‐ray radiation on synaptic properties HfO x :Mg(9%), a particular focus changes in linearity conductance updating. is achieved by introducing electrochemical impedance spectroscopy (EIS) to analyze variations oxygen‐deficient conductive filaments. Results show that increasing dose (0–1 Mrad(Si)) decreases high‐resistance state current during long‐term depression, reducing linearity. X‐ray photoelectron reveals increased oxygen vacancies postirradiation, while EIS indicates these hinder filament rupture, causing damage. research enhances understanding effects supports development radiation‐resistant synapses.

Язык: Английский

Процитировано

0

Flexible Tunable‐Plasticity Synaptic Transistors for Mimicking Dynamic Cognition and Reservoir Computing DOI

Sixin Zhang,

Jiahao Zhu, Rui Qiu

и другие.

Advanced Materials, Год журнала: 2025, Номер unknown

Опубликована: Апрель 9, 2025

Abstract Inspired by biological systems, neuromorphic computing can process extensive data and complex tasks more efficiently than traditional architectures. Artificial synaptic devices, serving as fundamental components in computing, needto closely mimic characteristics construct neural network systems. However, most existing multifunctional synapse devices are structurally lack tunability, making them unsuitable for building smarter In this work, a flexible tunable‐plasticity transistor (TST) is realized with memory modulation capabilities using indium gallium zinc oxide channel hybrid layer of polyimide Al 2 O 3 dielectric. The TST exhibits novel transition from short‐term plasticity to long‐term one adjusting stimulus amplitude, mirroring dynamic human forgetting behaviors across various scenarios. A system low non‐linearity wide range conductance variations constructed, it demonstrates 94.1% recognition rate on classical datasets. reservoir 4‐bit coding also developed, which significantly reduces computational complexity size without sacrificing accuracy. the work foundation intelligent efficient

Язык: Английский

Процитировано

0

Reimagining Robots: The Future of Cybernetic Organisms with Energy-Efficient Designs DOI Creative Commons
Stefan Stavrev

Big Data and Cognitive Computing, Год журнала: 2025, Номер 9(4), С. 104 - 104

Опубликована: Апрель 17, 2025

The development of cybernetic organisms—autonomous systems capable self-regulation and dynamic environmental interaction—requires innovations in both energy efficiency computational adaptability. This study explores the integration bio-inspired liquid flow batteries neuromorphic computing architectures to enable real-time learning power optimization autonomous robotic systems. Liquid-based storage systems, modeled after vascular networks, offer distributed management, reducing bottlenecks improving resilience long-duration operations. Complementing this, architectures, including memristor-based processors spiking neural networks (SNNs), enhance while minimizing consumption. By integrating these adaptive robots can dynamically allocate processing resources based on demands, bridging gap between biological artificial intelligence. evaluates feasibility technologies into platforms, assessing capacity, operational scalability. While show promise latency constraints, challenges remain electrolyte stability, framework standardization, real-world implementation. Future research must focus hybrid self-regulating distribution, material optimizations adaptability organisms. addressing challenges, this outlines a roadmap for reimagining robotics through principles, paving way applications healthcare, industrial automation, space exploration, environments.

Язык: Английский

Процитировано

0

High‐Efficiency Optoelectronic Modulation in Quasi‐2D Perovskite‐Based Transistors for Neuromorphic Computing DOI Creative Commons
Wenwen Wang, Yao Li,

J. Zhang

и другие.

Advanced Electronic Materials, Год журнала: 2025, Номер unknown

Опубликована: Май 5, 2025

Abstract Optoelectronic modulated transistors based on organic–inorganic halide perovskites can perceive and parse visual information, making them appealing for neuromorphic computing or future vision automation owing to their abundant tunable optoelectronic properties, high quantum efficiency, large specific surface area. Herein, quasi‐2D (ThMA) 2 (MA) n‐1 Pb n I 3n+1 ( = 4) transistor exhibits n/p‐type ambipolar transport characteristics. The remarkable hysteresis behavior observed in the transfer characteristics be by external voltages illumination. maximum charge mobility under light illumination with hole µ h ) of ≈1.5 × 10 −4 cm V −1 s (≈167 times higher than that dark condition), threshold voltage th 2.1 V, subthreshold swing SS 3.4 decade p‐channel mode, electron e ≈1.9 , 3.1 1.7 n‐channel respectively. effects potentiation depression properties proposed device are discussed. Chinese handwritten characters from Institute Automation Academy Sciences used simulate image recognition properties. perovskite offers a new platform development systems bionic vision.

Язык: Английский

Процитировано

0

All-optical synaptic devices utilizing 2D polymer film for logic operations and integrated edge computing DOI Creative Commons

Jinyong Li,

Jian Bi, Xiang Ma

и другие.

Cell Reports Physical Science, Год журнала: 2025, Номер unknown, С. 102570 - 102570

Опубликована: Май 1, 2025

Язык: Английский

Процитировано

0