Related references
Note: Only part of the references are listed.A Biological-Realtime Neuromorphic System in 28 nm CMOS Using Low-Leakage Switched Capacitor Circuits
Christian Mayr et al.
IEEE TRANSACTIONS ON BIOMEDICAL CIRCUITS AND SYSTEMS (2016)
Feedforward Categorization on AER Motion Events Using Cortex-Like Features in a Spiking Neural Network
Bo Zhao et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2015)
A framework for plasticity implementation on the SpiNNaker neural architecture
Francesco Galluppi et al.
FRONTIERS IN NEUROSCIENCE (2015)
Minitaur, an Event-Driven FPGA-Based Spiking Network Accelerator
Daniel Neil et al.
IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS (2014)
Tunable Low Energy, Compact and High Performance Neuromorphic Circuit for Spike-Based Synaptic Plasticity
Mostafa Rahimi Azghadi et al.
PLOS ONE (2014)
Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations
Ben Varkey Benjamin et al.
PROCEEDINGS OF THE IEEE (2014)
Spike-Based Synaptic Plasticity in Silicon: Design, Implementation, Application, and Challenges
Mostafa Rahimi Azghadi et al.
PROCEEDINGS OF THE IEEE (2014)
A million spiking-neuron integrated circuit with a scalable communication network and interface
Paul A. Merolla et al.
SCIENCE (2014)
Event-driven contrastive divergence for spiking neuromorphic systems
Emre Neftci et al.
FRONTIERS IN NEUROSCIENCE (2014)
Immunity to Device Variations in a Spiking Neural Network With Memristive Nanodevices
Damien Querlioz et al.
IEEE TRANSACTIONS ON NANOTECHNOLOGY (2013)
Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule
Michael Beyeler et al.
NEURAL NETWORKS (2013)
Bayesian Computation Emerges in Generic Cortical Microcircuits through Spike-Timing-Dependent Plasticity
Bernhard Nessler et al.
PLOS COMPUTATIONAL BIOLOGY (2013)
Real-time classification and sensor fusion with a spiking deep belief network
Peter O'Connor et al.
FRONTIERS IN NEUROSCIENCE (2013)
Extraction of temporally correlated features from dynamic vision sensors with spike-timing-dependent plasticity
Olivier Bichler et al.
NEURAL NETWORKS (2012)
Brain and high metabolic rate organ mass: contributions to resting energy expenditure beyond fat-free mass
Fahad Javed et al.
AMERICAN JOURNAL OF CLINICAL NUTRITION (2010)
A 128x128 120 dB 15 μs latency asynchronous temporal contrast vision sensor
Patrick Lichtsteiner et al.
IEEE JOURNAL OF SOLID-STATE CIRCUITS (2008)
Brian: a simulator for spiking neural networks in Python
Dan Goodman
Frontiers in Neuroinformatics (2008)
Learning real-world stimuli in a neural network with spike-driven synaptic dynamics
Joseph M. Brader et al.
NEURAL COMPUTATION (2007)
Spike-timing-dependent plasticity in balanced random networks
Abigail Morrison et al.
NEURAL COMPUTATION (2007)
Unsupervised learning of visual features through spike timing dependent plasticity
Timothee Masquelier et al.
PLOS COMPUTATIONAL BIOLOGY (2007)
Triplets of spikes in a model of spike timing-dependent plasticity
Jean-Pascal Pfister et al.
JOURNAL OF NEUROSCIENCE (2006)
Reducing the dimensionality of data with neural networks
G. E. Hinton et al.
SCIENCE (2006)
A VLSI array of low-power spiking neurons and bistable synapses with spike-timing dependent plasticity
G Indiveri et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2006)
Homeostatic plasticity in the developing nervous system
GG Turrigiano et al.
NATURE REVIEWS NEUROSCIENCE (2004)
Share Paper
