Results 91 to 100 of about 6,675,279 (300)

Bifurcations of emergent bursting in a neuronal network [PDF]

, 2012
Complex neuronal networks are an important tool to help explain paradoxical phenomena observed in biological recordings. Here we present a general approach to mathematically tackle a complex neuronal network so that we can fully understand the underlying
Wu Yu, Lu Wenlian, Wei Lin, Lin Wei, Lin, Wei, Wenlian Lu, Gareth Leng, Wu, Yu, Leng Gareth, Feng, Jianfeng, Jianfeng Feng, Leng, Gareth, Yu Wu, Lu, Wenlian, Feng Jianfeng   +14 more
core   +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

BindsNET: A Machine Learning-Oriented Spiking Neural Networks Library in Python

Frontiers in Neuroinformatics, 2018
The development of spiking neural network simulation software is a critical component enabling the modeling of neural systems and the development of biologically inspired algorithms.
Hananel Hazan, Daniel J. Saunders, Hassaan Khan, Devdhar Patel, Darpan T. Sanghavi, Hava T. Siegelmann, Robert Kozma   +6 more
doaj   +1 more source

Engineered Nanotopography to Modulate Growth and Signaling of Neuronal Networks

Advanced Functional Materials, EarlyView.
This study examines the interaction between neurons and nanoscale topographies on engineered substrates. Neurons cultured on nanowires, nanopillars and nanoneedles exhibit enhanced neurite outgrowth, form more organized neuronal circuits, and display improved synaptic connectivity, compared to flat substrates.
Hao Nguyen Tran, Kalyan Shobhana, Zlatan Trifunovic, Dan Smith, Michael Stuiber, Chennupati Jagadish, Mirella Dottori, Andrea J. O'Connor, Vini Gautam   +8 more
wiley   +1 more source

A Spiking Neuron and Population Model Based on the Growth Transform Dynamical System

Frontiers in Neuroscience, 2020
In neuromorphic engineering, neural populations are generally modeled in a bottom-up manner, where individual neuron models are connected through synapses to form large-scale spiking networks.
Ahana Gangopadhyay, Darshit Mehta, Shantanu Chakrabartty   +2 more
doaj   +1 more source

Spiking-UNet: Spiking Neural Networks for Spectrum Occupancy Monitoring

, 2023
With the exponential growth of the Internet of Things (IoT) landscape and the resulting spectrum congestion, innovative techniques for spectrum monitoring are crucial.
Akram Al-Hourani (12877233), Kosta Dakic (14858707), Bassel Al Homssi (12877226)   +2 more
core   +1 more source

Reservoir‐Driven Neuromorphic Computing Based on Composite Rare‐Earth/Transition Metal Oxide Memristor

Advanced Functional Materials, EarlyView.
A defect‐engineered Ag/Gd2O3:Nb2O5/Pt rare earth composite oxide memristor enables stable multilevel reservoir states through pulse driven conductance modulation. Experimentally measured device responses are incorporated into a device aware reservoir computing framework for CIFAR‐100 image classification, highlighting the potential of rare earth ...
Hammad Ghazanfar, Haider Abbas, Muhammad Rabeel, Honggyun Kim, Ghulam Dastgeer, Muhammad Nasim, Furqan Zahoor, Yawar Abbas, Waqas Ahmad, Deok‐kee Kim   +9 more
wiley   +1 more source

High-performance deep spiking neural networks with 0.3 spikes per neuron

Nature Communications
Communication by rare, binary spikes is a key factor for the energy efficiency of biological brains. However, it is harder to train biologically-inspired spiking neural networks than artificial neural networks.
Ana Stanojevic, Stanisław Woźniak, Guillaume Bellec, Giovanni Cherubini, Angeliki Pantazi, Wulfram Gerstner   +5 more
doaj   +1 more source

A Spiking Bidirectional Associative Memory Neural Network

, 2021
Spiking neural networks (SNNs) are a more biologically realistic model of the brain than traditional analog neural networks and therefore should be better for modelling certain functions of the human brain. This thesis uses the concept of deriving an SNN
Johnson, Melissa
core   +1 more source

Architecture‐Driven Functional Coupling in Vertically Aligned Nanocomposites

Advanced Functional Materials, EarlyView.
Vertically aligned nanocomposites define a growth‐engineered architecture in which vertical interfaces, strain fields, defect pathways, and phase connectivity are created simultaneously. This review shows how these architectural features couple ferroic, optical, ionic, electrochemical, and device responses, establishing design rules and open challenges
Md Shatil Islam‐Shanto, Javier Zamudio‐García, Abraham Sánchez‐Caballero, David Marrero‐López, Vincenzo Esposito   +4 more
wiley   +1 more source