Пакет: python-brian (1.4.3-1)

Ссылки для python-brian

Ресурсы Trisquel:

Исходный код brian:

Сопровождающий:

NeuroDebian Team

Original Maintainers:

NeuroDebian Team
Yaroslav Halchenko
Michael Hanke

Внешние ресурсы:

Сайт [www.briansimulator.org]

Подобные пакеты:

simulator for spiking neural networks

Brian is a clock-driven simulator for spiking neural networks. It is designed with an emphasis on flexibility and extensibility, for rapid development and refinement of neural models. Neuron models are specified by sets of user-specified differential equations, threshold conditions and reset conditions (given as strings). The focus is primarily on networks of single compartment neuron models (e.g. leaky integrate-and-fire or Hodgkin-Huxley type neurons). Features include:

 - a system for specifying quantities with physical dimensions
 - exact numerical integration for linear differential equations
 - Euler, Runge-Kutta and exponential Euler integration for nonlinear
   differential equations
 - synaptic connections with delays
 - short-term and long-term plasticity (spike-timing dependent plasticity)
 - a library of standard model components, including integrate-and-fire
   equations, synapses and ionic currents
 - a toolbox for automatically fitting spiking neuron models to
   electrophysiological recordings

Другие пакеты, относящиеся к python-brian

зависимости

рекомендации

предложения

dep: python

interactive high-level object-oriented language (default version)
dep: python-brian-lib (>= 1.4.3-1)

simulator for spiking neural networks -- extensions
dep: python-matplotlib (>= 0.90.1)

Python based plotting system in a style similar to Matlab
dep: python-numpy (>= 1.3.0)

Numerical Python adds a fast array facility to the Python language
dep: python-scipy (>= 0.7.0)

scientific tools for Python

rec: python-sympy

Computer Algebra System (CAS) in Python

sug: python-brian-doc

simulator for spiking neural networks - documentation
sug: python-cherrypy

Python web development framework
sug: python-nose

test discovery and running of Python's unittest

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