Neuro-inspired electronic skin for robots

F Liu, S Deswal, A Christou, Y Sandamirskaya… - Science robotics, 2022 - science.org
Touch is a complex sensing modality owing to large number of receptors (mechano, thermal,
pain) nonuniformly embedded in the soft skin all over the body. These receptors can gather …

Exploring neuromorphic computing based on spiking neural networks: Algorithms to hardware

N Rathi, I Chakraborty, A Kosta, A Sengupta… - ACM Computing …, 2023 - dl.acm.org
Neuromorphic Computing, a concept pioneered in the late 1980s, is receiving a lot of
attention lately due to its promise of reducing the computational energy, latency, as well as …

2022 roadmap on neuromorphic computing and engineering

DV Christensen, R Dittmann… - Neuromorphic …, 2022 - iopscience.iop.org
Modern computation based on von Neumann architecture is now a mature cutting-edge
science. In the von Neumann architecture, processing and memory units are implemented …

A comprehensive review on emerging artificial neuromorphic devices

J Zhu, T Zhang, Y Yang, R Huang - Applied Physics Reviews, 2020 - pubs.aip.org
The rapid development of information technology has led to urgent requirements for high
efficiency and ultralow power consumption. In the past few decades, neuromorphic …

Neuromorphic engineering: from biological to spike‐based hardware nervous systems

JQ Yang, R Wang, Y Ren, JY Mao, ZP Wang… - Advanced …, 2020 - Wiley Online Library
The human brain is a sophisticated, high‐performance biocomputer that processes multiple
complex tasks in parallel with high efficiency and remarkably low power consumption …

A survey of neuromorphic computing and neural networks in hardware

CD Schuman, TE Potok, RM Patton, JD Birdwell… - arXiv preprint arXiv …, 2017 - arxiv.org
Neuromorphic computing has come to refer to a variety of brain-inspired computers, devices,
and models that contrast the pervasive von Neumann computer architecture. This …

Memristors for energy‐efficient new computing paradigms

DS Jeong, KM Kim, S Kim, BJ Choi… - Advanced Electronic …, 2016 - Wiley Online Library
In this Review, memristors are examined from the frameworks of both von Neumann and
neuromorphic computing architectures. For the former, a new logic computational process …

Neuromorphic silicon neuron circuits

G Indiveri, B Linares-Barranco, TJ Hamilton… - Frontiers in …, 2011 - frontiersin.org
Hardware implementations of spiking neurons can be extremely useful for a large variety of
applications, ranging from high-speed modeling of large-scale neural systems to real-time …

An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation

A Shaban, SS Bezugam, M Suri - Nature Communications, 2021 - nature.com
Abstract We propose a Double EXponential Adaptive Threshold (DEXAT) neuron model that
improves the performance of neuromorphic Recurrent Spiking Neural Networks (RSNNs) by …

Artificial neural networks in hardware: A survey of two decades of progress

J Misra, I Saha - Neurocomputing, 2010 - Elsevier
This article presents a comprehensive overview of the hardware realizations of artificial
neural network (ANN) models, known as hardware neural networks (HNN), appearing in …