“Neuromorphic engineering” papers

Amidst the promises offered by projects with major chunks of funding in neuromorphic engineering like HBP, BrainScaleS, SpiNNaker, and TrueNorth, this research topic offers a refreshing glimpse into some of the current actual accomplishments in neuromorphic systems engineering and applications.

Cited by 4Open access

Editorial: Neuromorphic engineering for robotics

Zhenshan Bing, Chenguang Yang, Alois Knoll · Frontiers in Neurorobotics · 2023

Firstly, the success and limitation of deep neural networks greatly inspire the research potential that 5 biological intelligence can further boost the computing performance of artificial intelligence in terms of 6 data, power, and computing efficiency. Second, the emergence of novel neuromorphic hardware and sensors 7 has shown greater application-level performance compared with conventional CPU and GPU. Third, the 8 pace of progress in neuroscience has accelerated dramatically in recent years, providing a wealth of new 9 understanding and insights about the functioning of brains at the neuron level. Neuromorphic engineering 10 therefore can represent a fundamental revolution for robotics in many ways. We publish this research 11 topic to collect theoretical and experimental results dealing with neuromorphic engineering technologies 12 for the design, control, and real-world applications of robotic systems. After carefully and professionally 13 reviewing all submissions, four high-quality manuscripts are accepted. Below is a review of the articles 14 published in this collection. Overall, we hope that this topic can provide some references and novel ideas for the study of neuromorphic

Cited by 0Open access

Recent trends in neuromorphic engineering

Soman, Sumit, Jayadeva, Manan Suri · Figshare · 2019

Abstract Neuromorphic Engineering has emerged as an exciting research area, primarily owing to the paradigm shift from conventional computing architectures to data-driven, cognitive computing. There is a diversity of work in the literature pertaining to neuromorphic systems, devices and circuits. This review looks at recent trends in neuromorphic engineering and its sub-domains, with an attempt to identify key research directions that would assume significance in the future. We hope that this review would serve as a handy reference to both beginners and experts, and provide a glimpse into the broad spectrum of applications of neuromorphic hardware and algorithms. Our survey indicates that neuromorphic engineering holds a promising future, particularly with growing data volumes, and the imminent need for intelligent, versatile computing.

Cited by 0Open access

Neuromorphic engineering: overview and potential

Carver Mead, Gary Moore, Bartlett D. Moore · Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005. · 2006

Summary form only given. It is evident to even the most casual observer that the nervous systems of animals are able to accomplish feats that cannot be approached by our most powerful computing systems. Given the exponential increase in computing power over the last 45 years, our inability to rival the common housefly has become downright embarrassing. What is going on?.

Cited by 6

Neuromorphic Engineering Systems and Applications

Frontiers research topics · 2021

The Neuromorphic Engineering community benefits from continuous dialogue with the neuroscience and modelling communities. The CapoCaccia Cognitive Neuromorphic Engineering Workshop fosters this connection, promoting discussions on fundamental research questions from neuroscience, modelling, applications and hardware perspectives. With this research topic, we aim at showcasing how the continuous interplay between these disciplines leads to efficient computing technologies and a better understanding of neuroscience.Relevant topics include:• Neuromorphic hardware implementing neural primitives, supporting communication and implementing a neuromorphic substrate for computation and learning, including circuits in ASIC, FPGA development, system level development• Applications of neuromorphic hardware addressing perception or analysis of information, learning, decision making and control, including robotics, medical and prosthetic applications• Models inspired by neuroscience work and applied to neuromorphic hardware• Theoretical work aimed at harnessing event-based sensing, computing and control• Review articles centred around the topics discussed at the Capo Caccia Cognitive Neuromorphic Engineering Workshop

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Recent trends in neuromorphic engineering

Sumit Soman, Jayadeva Jayadeva, Manan Suri · Big Data Analytics · 2016

Neuromorphic Engineering has emerged as an exciting research area, primarily owing to the paradigm shift from conventional computing architectures to data-driven, cognitive computing. There is a diversity of work in the literature pertaining to neuromorphic systems, devices and circuits. This review looks at recent trends in neuromorphic engineering and its sub-domains, with an attempt to identify key research directions that would assume significance in the future. We hope that this review would serve as a handy reference to both beginners and experts, and provide a glimpse into the broad spectrum of applications of neuromorphic hardware and algorithms. Our survey indicates that neuromorphic engineering holds a promising future, particularly with growing data volumes, and the imminent need for intelligent, versatile computing.

Cited by 44Open access

Recent trends in neuromorphic engineering

Soman, Sumit, Jayadeva, Manan Suri · Figshare · 2019

Abstract Neuromorphic Engineering has emerged as an exciting research area, primarily owing to the paradigm shift from conventional computing architectures to data-driven, cognitive computing. There is a diversity of work in the literature pertaining to neuromorphic systems, devices and circuits. This review looks at recent trends in neuromorphic engineering and its sub-domains, with an attempt to identify key research directions that would assume significance in the future. We hope that this review would serve as a handy reference to both beginners and experts, and provide a glimpse into the broad spectrum of applications of neuromorphic hardware and algorithms. Our survey indicates that neuromorphic engineering holds a promising future, particularly with growing data volumes, and the imminent need for intelligent, versatile computing.

Cited by 0Open access

Neuromorphic Engineering Systems and Applications

Jennifer Hasler, Tobi Delbruck, Andre van Schaik · Directory of Open access Books (OAPEN Foundation) · 2015

Neuromorphic engineering has just reached its 25th year as a discipline. In the first two decades neuromorphic engineers focused on building models of sensors, such as silicon cochleas and retinas, and building blocks such as silicon neurons and synapses. These designs have honed our skills in implementing sensors and neural networks in VLSI using analog and mixed mode circuits. Over the last decade the address event representation has been used to interface devices and computers from different designers and even different groups. This facility has been essential for our ability to combine sensors, neural networks, and actuators into neuromorphic systems. More recently, several big projects have emerged to build very large scale neuromorphic systems. The Telluride Neuromorphic Engineering Workshop (since 1994) and the CapoCaccia Cognitive Neuromorphic Engineering Workshop (since 2009) have been instrumental not only in creating a strongly connected research community, but also in introducing different groups to each otherâs hardware. Many neuromorphic systems are first created at one of these workshops. With this special research topic, we showcase the state-of-the-art in neuromorphic systems.

Cited by 0Open access

Introducing ‘Neuromorphic Computing and Engineering’

Giacomo Indiveri · Neuromorphic Computing and Engineering · 2021

Abstract The standard nature of computing is currently being challenged by a range of problems that start to hinder technological progress. One of the strategies being proposed to address some of these problems is to develop novel brain-inspired processing methods and technologies, and apply them to a wide range of application scenarios. This is an extremely challenging endeavor that requires researchers in multiple disciplines to combine their efforts and simultaneously co-design the processing methods, the supporting computing architectures, and their underlying technologies. The journal ‘Neuromorphic Computing and Engineering’ (NCE) has been launched to support this new community in this effort and provide a forum and repository for presenting and discussing its latest advances. Through close collaboration with our colleagues on the editorial team, the scope and characteristics of NCE have been designed to ensure it serves a growing transdisciplinary and dynamic community across academia and industry.

Cited by 33Open access

Neuromorphic chips for biomedical engineering

Kaiyang Wang, Shuhui Ren, Yunfang Jia et al. · Mechanobiology in Medicine · 2025

The modern medical field faces two critical challenges: the dramatic increase in data complexity and the explosive growth in data size. Especially in current research, medical diagnostic, and data processing devices relying on traditional computer architecture are increasingly showing limitations when faced with dynamic temporal and spatial processing requirements, as well as high-dimensional data processing tasks. Neuromorphic devices provide a new way for biomedical data processing due to their low energy consumption and high dynamic information processing capabilities. This paper aims to reveal the advantages of neuromorphic devices in biomedical applications. First, this review emphasizes the urgent need of biomedical engineering for diversify clinical diagnostic techniques. Secondly, the feasibility of the application in biomedical engineering is demonstrated by reviewing the historical development of neuromorphic devices from basic modeling to multimodal signal processing. In addition, this paper demonstrates the great potential of neuromorphic chips for application in the fields of biosensing technology, medical image processing and generation, rehabilitation medical engineering, and brain-computer interfaces. Finally, this review provides the pathways for constructing standardized experimental protocols using biocompatible technologies, personalized treatment strategies, and systematic clinical validation. In summary, neuromorphic devices will drive technological innovation in the biomedical field and make significant contributions to life health.

Cited by 4Open access

Neuroelectronic interface and neuromorphic engineering

Donhee Ham · 2023

Cited by 0

Recent trends in neuromorphic engineering

Sumit Soman, Jayadeva Jayadeva, Manan Suri · Greater South Information System · 2016

Neuromorphic Engineering has emerged as an exciting research area, primarily owing to the paradigm shift from conventional computing architectures to data-driven, cognitive computing. There is a diversity of work in the literature pertaining to neuromorphic systems, devices and circuits. This review looks at recent trends in neuromorphic engineering and its sub-domains, with an attempt to identify key research directions that would assume significance in the future. We hope that this review would serve as a handy reference to both beginners and experts, and provide a glimpse into the broad spectrum of applications of neuromorphic hardware and algorithms. Our survey indicates that neuromorphic engineering holds a promising future, particularly with growing data volumes, and the imminent need for intelligent, versatile computing.

Cited by 0Open access

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