Results 11 to 20 of about 169 (160)

2022 roadmap on neuromorphic computing and engineering [PDF]

Neuromorphic Computing and Engineering, 2022
Abstract 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 as separate blocks interchanging data intensively and continuously. This data transfer is responsible for a large part of the power consumption.
Dennis V. Christensen, Regina Dittmann, Bernabé Linares-Barranco, Abu Sebastian, Manuel Le Gallo, Andrea Redaelli, Stefan Slesazeck, Thomas Mikolajick, Sabina Spiga, Stephan Menzel, Ilia Valov, Gianluca Milano, Carlo Ricciardi, Shi-Jun Liang, Feng Miao, Mario Lanza, Tyler J. Quill, Scott T. Keene, Alberto Salleo, Julie Grollier, Danijela Markovic, Alice Mizrahi, Peng Yao, J. Joshua Yang, Giacomo Indiveri, John Paul Strachan, Suman Datta, Elisa Vianello, Alexandre Valentian, Johannes Feldmann, Xuan Li, Wolfram H. P. Pernice, Harish Bhaskaran, Steve B. Furber, Emre Neftci, Franz Scherr, Wolfgang Maass 0001, Srikanth Ramaswamy, Jonathan Tapson, Priyadarshini Panda, Youngeun Kim, Gouhei Tanaka, Simon Thorpe, Chiara Bartolozzi, Thomas A. Cleland, Christoph Posch, Shih-Chii Liu, Gabriella Panuccio, Mufti Mahmud, Arnab Neelim Mazumder, Morteza Hosseini, Tinoosh Mohsenin, Elisa Donati, Silvia Tolu, Roberto Galeazzi, Martin Ejsing Christensen, Sune Holm, Daniele Ielmini, Nini Pryds   +58 more
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Introducing ‘Neuromorphic Computing and Engineering’

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 ...
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Neuromorphic engineering: overview and potential [PDF]

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.
C. Mead, G. Moore, B. Moore
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Low‐Power Computing with Neuromorphic Engineering [PDF]

Advanced Intelligent Systems, 2020
The increasing power consumption in the existing computation architecture presents grand challenges for the performance and reliability of very‐large‐scale integrated circuits. Inspired by the characteristics of the human brain for processing complicated tasks with low power, neuromorphic computing is intensively investigated for decreasing power ...
Dingbang Liu, Hao Yu 0001, Yang Chai
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Editorial: Insights in neuromorphic engineering: 2021

Frontiers in Neuroscience, 2023
Peer ...
André van Schaik, Bernabé Linares-Barranco   +1 more
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Neuromorphic Engineering Needs Closed-Loop Benchmarks [PDF]

Frontiers in Neuroscience, 2022
Neuromorphic engineering aims to build (autonomous) systems by mimicking biological systems. It is motivated by the observation that biological organisms—from algae to primates—excel in sensing their environment, reacting promptly to their perils and opportunities.
Milde, Moritz B. (R19881), Afshar, Saeed (R17598), Xu, Ying (R19792), Marcireau, Alexandre (R19952), Joubert, Damien (R20048), Ramesh, Bharath (R20212), Bethi, Yeshwanth (S35160), Ralph, Nicholas O. (R20844), El Arja, Sami (S35426), Dennler, Nik, Schaik, Andre van (R16638), Cohen, Gregory (R18542)   +11 more
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Recent trends in neuromorphic engineering [PDF]

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.
Sumit Soman, Jayadeva Jayadeva, Manan Suri   +2 more
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Visualizing a joint future of neuroscience and neuromorphic engineering

Neuron, 2021
Recent research resolves the challenging problem of building biophysically plausible spiking neural models that are also capable of complex information processing. This advance creates new opportunities in neuroscience and neuromorphic engineering, which we discussed at an online focus meeting.
Friedemann Zenke, Sander M. Bohté, Claudia Clopath, Iulia M. Comşa, Julian Göltz, Wolfgang Maass, Timothée Masquelier, Richard Naud, Emre O. Neftci, Mihai A. Petrovici, Franz Scherr, Dan F.M. Goodman   +11 more
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Neuromorphic Engineering: In Memory of Misha Mahowald

Neural Computation, 2022
Abstract We review the coevolution of hardware and software dedicated to neuromorphic systems. From modest beginnings, these disciplines have become central to the larger field of computation. In the process, their biological foundations become more relevant, and their realizations increasingly overlap.
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Laser‐Induced Graphene from Waste Almond Shells

Advanced Functional Materials, EarlyView.
Almond shells, an abundant agricultural by‐product, are repurposed to create a fully bioderived almond shell/chitosan composite (ASC) degradable in soil. ASC is converted into laser‐induced graphene (LIG) by laser scribing and proposed as a substrate for transient electronics.
Yulia Steksova, Anna Chiara Bressi, Marina Galliani, Attilio Marino, Gianni Ciofani, Eduardo Machado‐Charry, Hilda Gomez Bernal, Alessandra Francini, Luca Sebastiani, Francesco Greco   +9 more
wiley   +1 more source