Results 171 to 180 of about 3,555,912 (299)

Expressivity of Spiking Neural Networks [PDF]

The synergy between spiking neural networks and neuromorphic hardware holds promise for the development of energy-efficient AI applications. Inspired by this potential, we revisit the foundational aspects to study the capabilities of spiking neural ...
Singh, Manjot, Fono, Adalbert, Kutyniok, Gitta   +2 more
core   +1 more source

An On‐Demand Neuromorphic Vision System Enabled by a Multi‐Paradigm Neuromorphic Device and Hierarchical Reconfigurability Designed from Device to System Level

Advanced Science, EarlyView.
An on‐demand ultra‐reconfigurable intelligent vision system with hierarchical reconfigurability from device to system levels is demonstrated. Through co‐design of a multi‐paradigm device, reconfigurable circuits, and adaptive system architecture/algorithms, the system enables seamless switching among spiking, non‐spiking, neuromorphic imaging (NI), and
Biyi Jiang, Jiayi Xu, Liang Ran, Xinhe Feng, Khalil Harrabi, Yida Li, Longyang Lin, Feichi Zhou   +7 more
wiley   +1 more source

Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing

Advanced Science, EarlyView.
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale, Marie Celine Lefevre, Alessio Carmignani, Maria Cristina Ceccarelli, Matteo Battaglini, Attilio Marino, Gianni Ciofani   +6 more
wiley   +1 more source

Magnetoelectric Nanoparticle‐Based Wireless Brain–Computer Interface: Underlying Physics and Projected Technology Pathway

Advanced Science, EarlyView.
Magnetoelectric nanoparticles (MENPs) enable fully wireless, minutely invasive neuromodulation, and potentially neural recording, by converting magnetic into electric and, conversely, electric into magnetic fields, respectively, at high spatiotemporal resolution.
Elric Zhang, Max Shotbolt, Mostafa Abdel‐Mottaleb, Shawnus Chen, Victoria Andre, Jieyuan Tian, Jonathan Shulgach, Max Murphy, Brian Noga, Ping Liang, Darcy Griffin, Douglas Weber, Marta Pardo, Salvador Pane, Sakhrat Khizroev   +14 more
wiley   +1 more source

The role of inhibition in modeling decision making with spiking neural networks. [PDF]

Front Neuroinform
Król-Józaga B, Duggins P, Broniec-Wójcik A, Wichary S.   +3 more
europepmc   +1 more source

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source

Wheel Slip Regulation Using Fuzzy Spiking Neural Networks

, 2016
International Joint Conference on Neural Networks (IJCNN) -- JUL 24-29, 2016 -- Vancouver, CANADAIn this paper, a fuzzy spiking neural network structure is developed for the wheel slip regulation problem of an Antilock Braking System.
Oniz, Yesim, Kaynak, Okyay
core   +1 more source

Multi-plasticity synergy with adaptive mechanism assignment for training spiking neural networks. [PDF]

Front Neurosci
Li Z, Wang H, Liu Y, Ma C, Gordleeva S, Yu Q.   +5 more
europepmc   +1 more source

Functional Disorder at the Neural Interface: How Disordered Nanostructures Promote Proper Growth and Differentiation in In Vitro Neural Cultures

Advanced Science, EarlyView.
This work provides a practical guide for neuroengineers to design advanced neural interfaces, embracing and tailoring the concept of functional disorder. By bridging 2D and 3D in vitro models, this work highlights how non‐periodic, spatially heterogeneous, multiscale nanotopography can enable more physiologically relevant platforms for studying neural ...
F. Maita, E. Palmieri, I. Lucarini, L. Montaina, L. Maiolo   +4 more
wiley   +1 more source

Backpropagation-free spiking neural networks with the forward-forward algorithm. [PDF]

Sci Rep
Ghader M, Kheradpisheh SR, Farahani B, Fazlali M.   +3 more
europepmc   +1 more source