Exploring neuromorphic computing based on spiking neural networks: Algorithms to hardware
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 …
attention lately due to its promise of reducing the computational energy, latency, as well as …
Memristors for energy‐efficient new computing paradigms
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 computing architectures. For the former, a new logic computational process …
Memory and information processing in neuromorphic systems
G Indiveri, SC Liu - Proceedings of the IEEE, 2015 - ieeexplore.ieee.org
A striking difference between brain-inspired neuromorphic processors and current von
Neumann processor architectures is the way in which memory and processing is organized …
Neumann processor architectures is the way in which memory and processing is organized …
Experimental demonstration of a second-order memristor and its ability to biorealistically implement synaptic plasticity
Memristors have been extensively studied for data storage and low-power computation
applications. In this study, we show that memristors offer more than simple resistance …
applications. In this study, we show that memristors offer more than simple resistance …
Event-driven random back-propagation: Enabling neuromorphic deep learning machines
An ongoing challenge in neuromorphic computing is to devise general and computationally
efficient models of inference and learning which are compatible with the spatial and …
efficient models of inference and learning which are compatible with the spatial and …
A brain-inspired algorithm that mitigates catastrophic forgetting of artificial and spiking neural networks with low computational cost
Neuromodulators in the brain act globally at many forms of synaptic plasticity, represented
as metaplasticity, which is rarely considered by existing spiking (SNNs) and nonspiking …
as metaplasticity, which is rarely considered by existing spiking (SNNs) and nonspiking …
The spike-timing dependence of plasticity
DE Feldman - Neuron, 2012 - cell.com
In spike-timing-dependent plasticity (STDP), the order and precise temporal interval
between presynaptic and postsynaptic spikes determine the sign and magnitude of long …
between presynaptic and postsynaptic spikes determine the sign and magnitude of long …
Biorealistic implementation of synaptic functions with oxide memristors through internal ionic dynamics
Memristors have attracted broad interest as a promising candidate for future memory and
computing applications. Particularly, it is believed that memristors can effectively implement …
computing applications. Particularly, it is believed that memristors can effectively implement …
Environment and brain plasticity: towards an endogenous pharmacotherapy
Brain plasticity refers to the remarkable property of cerebral neurons to change their
structure and function in response to experience, a fundamental theoretical theme in the …
structure and function in response to experience, a fundamental theoretical theme in the …
Astrocytes: Orchestrating synaptic plasticity?
Synaptic plasticity is the capacity of a preexisting connection between two neurons to
change in strength as a function of neural activity. Because synaptic plasticity is the major …
change in strength as a function of neural activity. Because synaptic plasticity is the major …