• Spikenet

  • Referenced in 12 articles [sw08892]
  • modelling large networks of spiking neurons. Many biological neural network models face the problem ... difficult to assess the efficiency of these models to solve complex problems such as image ... spike discharge rate is low, millions of neurons and billions of connections can be modelled ... such a mechanism in SpikeNET, our neural network simulation package. The type of model...
  • Brian

  • Referenced in 29 articles [sw23588]
  • Brian” is a new simulator for spiking neural networks, written in Python (http://brian. di.ens.fr ... highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons...
  • NEST

  • Referenced in 32 articles [sw26849]
  • dynamics, size, and structure of neural systems rather than on the detailed morphological and biophysical ... Models of sensory processing e.g. in the visual or auditory cortex of mammals. Models ... network activity dynamics, e.g. in laminar cortical networks or random balanced networks. Models of spike...
  • CARLsim

  • Referenced in 1 article [sw30218]
  • library for simulating large-scale spiking neural network (SNN) models with a high degree ... detail. CARLsim allows execution of networks of Izhikevich spiking neurons with realistic synaptic dynamics...
  • BindsNET

  • Referenced in 1 article [sw30217]
  • spiking neural network simulation software is a critical component enabling the modeling of neural systems ... software frameworks support a wide range of neural functionality, software abstraction levels, and hardware devices ... Python package for the simulation of spiking neural networks, specifically geared towards machine learning...
  • hpHawkes

  • Referenced in 1 article [sw38753]
  • financial transactions, neural spike trains and the spread of memes through social networks. The usefulness ... these stochastic process models within a host of economic sectors and scientific disciplines is undercut...
  • SpineML

  • Referenced in 1 article [sw40078]
  • Spiking Neural Mark-up Language (SpineML) is a declarative XML based model description language ... large scale neural network models. It is partially based upon on the INCF NineML syntax...
  • ANNarchy

  • Referenced in 2 articles [sw30220]
  • neural simulator, which allows to easily define and simulate rate-coded and spiking networks ... models can be specified using an equation-oriented mathematical description similar to the Brian neural...
  • SNN toolbox

  • Referenced in 1 article [sw41929]
  • networks into spiking neural networks, and to run them using various spike encodings. A unique ... that it accepts input models from many different deep-learning libraries (Keras / TF, pytorch...
  • PCSIM

  • Referenced in 2 articles [sw12749]
  • distributed simulation of large scale networks of spiking point neurons. Although its computational core ... neural circuit simulator with data analysis and visualization tools to manage the full neural modeling...
  • SEFRON

  • Referenced in 1 article [sw41928]
  • physiological needs, the time-varying synapse model proposed in this paper allows the synaptic efficacy ... single SEFRON classifier with other spiking neural networks (SNNs) are also presented using four benchmark...
  • NEVESIM

  • Referenced in 1 article [sw39766]
  • stochastic spiking neurons from the recently developed theoretical framework of neural sampling. This functionality ... extensions that support simulation of various neural network models incorporating different neuron and synapse types...
  • S4NN

  • Referenced in 1 article [sw41327]
  • supervised learning rule for multilayer spiking neural networks (SNNs) that use a form of temporal ... coding scheme, all neurons fire exactly one spike per stimulus, but the firing order carries ... learning rule for this sort of network, named S4NN, akin to traditional error backpropagation ... computed backward in a feedforward network with any number of layers. This approach reaches state...
  • NxTF

  • Referenced in 1 article [sw38430]
  • Neural Networks on Intel Loihi. Spiking Neural Networks (SNNs) are a promising paradigm for efficient ... DNNs trained directly on spikes as well as models converted from traditional DNNs, processing both...
  • AnimatLab

  • Referenced in 1 article [sw23735]
  • combines biomechanical simulation and biologically realistic neural networks. You can build the body ... rate and leaky integrate and fire spiking neural models. In addition, there a number...
  • sPyNNaker

  • Referenced in 0 articles [sw37937]
  • package for simulating PyNN-defined spiking neural networks (SNNs) on the SpiNNaker neuromorphic platform. Operations ... pipelined event-driven spike processing. Preprocessing, realtime execution, and neuron/synapse model implementations are discussed...
  • ARfit

  • Referenced in 38 articles [sw00046]
  • ARfit is a collection of Matlab modules for...
  • Coq

  • Referenced in 1890 articles [sw00161]
  • Coq is a formal proof management system. It...
  • HSL

  • Referenced in 279 articles [sw00418]
  • HSL (formerly the Harwell Subroutine Library) is a...
  • LAPACK

  • Referenced in 1702 articles [sw00503]
  • LAPACK is written in Fortran 90 and provides...