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Neuromorphic engineering

Known as: Neuromorphic, Neuromorphic computing, Neuromorphics 
Neuromorphic engineering, also known as neuromorphic computing, is a concept developed by Carver Mead, in the late 1980s, describing the use of very… 
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Related topics

Related topics

25 relations
Analog computerArtificial neural networkBRAIN InitiativeComputer science

Broader (1)

Electrical engineering

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2009
2009
Exploiting memristance in adaptive asynchronous spiking neuromorphic nanotechnology systems
In this paper we show that Spike-Time-Dependent-Plasticity (STDP), a powerful learning paradigm for spiking neural systems, can… 
Review
2005
Review
2005
Afterlife for silicon: CMOL circuit architectures
This is a brief review of our recent work on architectures for the prospective hybrid CMOS/nanowire/ nanodevice ("CMOL") circuits… 
Highly Cited
2003
Highly Cited
2003
CrossNets: possible neuromorphic networks based on nanoscale components
Extremely dense neuromorphic networks may be based on hybrid 2D arrays of nanoscale components, including molecular latching… 
Review
2003
Review
2003
Electronics Below 10 nm
1997
1997
Analog VLSI Stochastic Perturbative Learning Architectures
We present analog VLSI neuromorphic architectures fora general class of learning tasks, which include supervised learning… 
1996
1996
Analog VLSI Circuits for Attention-Based, Visual Tracking
A one-dimensional visual tracking chip has been implemented using neuromorphic, analog VLSI techniques to model selective visual… 
1989
1989
A neuromorphic controller for a three-link biped robot
Summary form only given, as follows. A neural network architecture is developed for the control of a three-link biped walking… 
Highly Cited
1989
Highly Cited
1989
Microwave diversity imaging and automated target identification based on models of neural networks
Radar targets can be identified by either forming images with sufficient resolution to be recognized by the human observer or by… 
Highly Cited
1988
Highly Cited
1988
A trainable neuromorphic controller
On montre que les caracteristiques de calcul (telles la rapidite, le temps reel et la robustesse des performances) des reseaux… 
Highly Cited
1987
Highly Cited
1987
Stochastic Learning Networks and their Electronic Implementation
We describe a family of learning algorithms that operate on a recurrent, symmetrically connected, neuromorphic network that, like… 
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