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Spiking neural network

Known as: SNN, Spiking neural networks 
Spiking neural networks (SNNs) fall into the third generation of neural network models, increasing the level of realism in a neural simulation. In… 
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Related topics

Related topics

38 relations
ARM architectureAction potentialArtificial neural networkArtificial neuron

Broader (2)

Computational neuroscienceComputational statistics

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
The scalable spiking neural network automatic generation in MATLAB focused on the hardware implementation
In article development of the program in the environment of MATLAB is considered. The program allows to generate spiking neural… 
2015
2015
Spiking Neural Network Architecture
ARM microprocessors are found in nearly every consumer device, from smartphones to gameboxes to e-readers and digital televisions… 
2014
2014
Controlling articulated robots in task-space with spiking silicon neurons
Emulating how humans coordinate articulated limbs within the brain's power budget promises to accelerate progress in building… 
Highly Cited
2011
Highly Cited
2011
Training spiking neural models using cuckoo search algorithm
Several meta-heuristic algorithms have been proposed in the last years for solving a wide range of optimization problems. Cuckoo… 
Highly Cited
2007
Highly Cited
2007
Perceptual Control Based on Prediction for Natural Communication of a Partner Robot
This paper discusses a perceptual system for natural communication between a partner robot and a human. The prediction is very… 
2006
2006
Evolutionary design of spiking neural networks.
Unlike traditional artificial neural networks (ANNs), which use a high abstraction of real neurons, spiking neural networks (SNNs… 
2006
2006
Speech Emotion Recognition Using Spiking Neural Networks
Human social communication depends largely on exchanges of non-verbal signals, including non-lexical expression of emotions in… 
2005
2005
Empirical Bayes interpretations of random point events
Given a sequence of apparently random point events, such as neuronal spikes, one may interpret them as being derived either… 
2004
2004
Grey prediction based RBF neural network self-tuning PID control for turning process
Turning process is a system with the property of nonlinear, time varying, incalculability and uncertainty. Conventional PID… 
2002
2002
Convolutional spiking neural network model for robust face detection
We propose a convolutional spiking neural network (CSNN) model with population coding for robust face detection. The basic… 
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