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Traditional protection systems for microgrids, which rely on high fault currents and continuous communication, struggle to keep up with the changing dynamics and cybersecurity concerns of decentralized networks. In this study, we introduce…

Signal Processing · Electrical Eng. & Systems 2026-02-26 Saurabh Prabhakar , Bijaya Ketan Panigrahi , Frede Blaabjerg , Subham Sahoo

A new type of microfluidic system for biological cell manipulation, a CMOS/microfluidic hybrid, is demonstrated. The hybrid system starts with a custom-designed CMOS (complementary metal-oxide semiconductor) chip fabricated in a…

Quantitative Methods · Quantitative Biology 2007-05-23 Hakho Lee , Yong Liu , Donhee Ham , Robert M. Westervelt

I review the advancements of atomic scale nanoelectronics towards quantum neuromorphics. First, I summarize the key properties of elementary combinations of few neurons, namely long-- and short--term plasticity, spike-timing dependent…

Emerging Technologies · Computer Science 2016-09-21 Enrico Prati

Synapses are functional links between neurons, through which "information" flows in the neural network. These connections vary significantly in strength, typically resulting from the intrinsic heterogeneity in their chemical and biological…

Materials Science · Physics 2016-03-15 He Tian , Qiushi Guo , Yunjun Xie , Huan Zhao , Cheng Li , Judy J. Cha , Fengnian Xia , Han Wang

In this paper we present a simple microscopic stochastic model describing short term plasticity within a large homogeneous network of interacting neurons. Each neuron is represented by its membrane potential and by the residual calcium…

Probability · Mathematics 2020-01-29 Antonio Galves , Eva Löcherbach , Christophe Pouzat , Errico Presutti

Cell-based biosensors constitute a fundamental tool in biotechnology, and their relevance has greatly increased in recent years as a result of a surging demand for reduced animal testing and for high-throughput and cost-effective in vitro…

We present a quantitative analysis of the steady state electronic transport in a resistive switching device. The device is composed of a thin film of Ag$_{2}$S (solid electrolyte) contacted by a Pt nano-contact acting as ion-blocking…

Materials Science · Physics 2017-12-11 Monica Morales-Masis , Hans-Dieter Wiemhofer , Jan M. van Ruitenbeek

Neuromorphic computing which aims to mimic the collective and emergent behavior of the brain's neurons, synapses, axons, dendrites offers an intriguing, potentially disruptive solution to society's ever-growing computational needs. Although…

Applied Physics · Physics 2021-08-31 Uday S. Goteti , Ivan A. Zaluzhnyy , Shriram Ramanathan , Robert C. Dynes , Alex Frano

Reversible bipolar nano-switches that can be set and read electronically in a solid-state two-terminal device are very promising for applications. We have performed molecular-dynamics simulations that mimic systems with oxygen vacancies…

Mesoscale and Nanoscale Physics · Physics 2015-05-20 S. E. Savel'ev , A. S. Alexandrov , A. M. Bratkovsky , R. Stanley Williams

Neuromorphic computing --- brainlike computing in hardware --- typically requires myriad CMOS spiking neurons interconnected by a dense mesh of nanoscale plastic synapses. Memristors are frequently citepd as strong synapse candidates due to…

Neural and Evolutionary Computing · Computer Science 2015-09-02 David Howard , Larry Bull , Ben De Lacy Costello

Homeostatic plasticity is a stabilizing mechanism that allows neural systems to maintain their activity around a functional operating point. This is an extremely useful mechanism for neuromorphic computing systems, as it can be used to…

Emerging Technologies · Computer Science 2019-08-21 Ning Qiao , Giacomo Indiveri , Chiara Bartolozzi

Heterogeneous systems with analog CMOS circuits integrated with nanoscale memristive devices enable efficient deployment of neural networks on neuromorphic hardware. CMOS Neuron with low footprint can emulate slow temporal dynamics by…

Future brain-computer interfaces will require local and highly individualized signal processing of fully integrated electronic circuits within the nervous system and other living tissue. New devices will need to be developed that can…

Over the past decade Spiking Neural Networks (SNN) have emerged as one of the popular architectures to emulate the brain. In SNN, information is temporally encoded and communication between neurons is accomplished by means of spikes. In…

Emerging Technologies · Computer Science 2016-12-14 Abhronil Sengupta , Aparajita Banerjee , Kaushik Roy

Recent advancements in head-mounted wearable technology are revolutionizing the field of biopotential measurement, but the integration of these technologies into practical, user-friendly devices remains challenging due to issues with design…

Neuromorphic computing based on spiking neural networks has the potential to significantly improve on-line learning capabilities and energy efficiency of artificial intelligence, specially for edge computing. Recent progress in…

Applied Physics · Physics 2021-11-04 Yann Beilliard , Fabien Alibart

Flexible metal oxide/graphene oxide hybrid multi-gate neuron transistors were fabricated on flexible graphene substrates. Dendritic integrations in both spatial and temporal modes were successfully emulated, and spatiotemporal correlated…

Neurons and Cognition · Quantitative Biology 2016-09-02 Chang Jin Wan , Wei Wang , Li Qiang Zhu , Yang Hui Liu , Ping Feng , Zhao Ping Liu , Yi Shi , Qing Wan

Networks of living neurons exhibit an avalanche mode of activity, experimentally found in organotypic cultures. Here we present a model based on self-organized criticality and taking into account brain plasticity, which is able to reproduce…

Neurons and Cognition · Quantitative Biology 2009-11-13 Lucilla de Arcangelis , Carla Perrone-Capano , Hans J. Herrmann

Biological neurons are electro-mechanical systems, where the generation and propagation of an action potential is coupled to generation and transmission of an acoustic wave. Neuristors, such as VO2, characterized by insulator-metal…

Orchestration of diverse synaptic plasticity mechanisms across different timescales produces complex cognitive processes. To achieve comparable cognitive complexity in memristive neuromorphic systems, devices that are capable to emulate…