首页| JavaScript| HTML/CSS| Matlab| PHP| Python| Java| C/C++/VC++| C#| ASP| 其他|
购买积分 购买会员 激活码充值

您现在的位置是:虫虫源码 > 其他 > pysnn的使用

pysnn的使用

  • 资源大小:18.34 MB
  • 上传时间:2021-06-30
  • 下载次数:0次
  • 浏览次数:0次
  • 资源积分:1积分
  • 标      签: pysnn

资 源 简 介

# __PySNN__ [![Build Status](https://travis-ci.com/BasBuller/PySNN.svg?branch=master)](https://travis-ci.com/BasBuller/PySNN) [![codecov.io](https://codecov.io/gh/BasBuller/PySNN/coverage.svg?branch=master)](https://codecov.io/gh/BasBuller/PySNN) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) Spiking neural network (SNN) framework written on top of PyTorch for efficient simulation of SNNs both on _**CPU**_ and _**GPU**_. The framework is intended for with correlation based learning methods. The library adheres to the highly modular and dynamic design of PyTorch, and does not require its user to learn a new framework. *This framework"s power lies in the ease of defining and mixing new Neuron and Connection objects that seamlessly work to

文 件 列 表

PySNN-master
.coveragerc
.github
.gitignore
.pre-commit-config.yaml
.travis.yml
CONTRIBUTING.md
LICENSE
README.md
docs
docsrc
examples
pysnn
setup.py
tests

相 关 资 源

VIP VIP
0.197978s