Metadata-Version: 1.1
Name: neuralkernel
Version: 0.0.3
Summary: neural networks as a general-purpose computational framework
Home-page: UNKNOWN
Author: Noah Stebbins
Author-email: nstebbins1@gmail.com
License: MIT
Description-Content-Type: UNKNOWN
Description: # Neuralkernel
        [![Build Status](https://travis-ci.org/nstebbins/neuralkernel.svg?branch=master)](https://travis-ci.org/nstebbins/neuralkernel)
        [![PyPI](https://img.shields.io/pypi/v/neuralkernel.svg)](https://pypi.python.org/pypi/neuralkernel)
        [![PyPI - License](https://img.shields.io/pypi/l/neuralkernel.svg)](https://pypi.python.org/pypi/neuralkernel)
        [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/neuralkernel.svg)](https://pypi.python.org/pypi/neuralkernel)
        
        This project uses networks of neuron-like computational units to build a framework of computation. Specifically, it implements characteristics traditionally found in neural networks including synaptic diversity, temporal delays, and voltage spikes. It builds on the ideas proposed in the paper [STICK: Spike Time Interval Computational Kernel, A Framework for General Purpose Computation](https://arxiv.org/abs/1507.06222).
        
        ## Getting Started
        
        To run a sample network, you can run the module.
        
        ```bash
        python -m neuralkernel
        ```
        
        The networks currently implemented are:
        
        * Inverting Memory
        * Logarithm
        * Maximum
        * Non-Inverting Memory
        * Full Subtractor
        
        For more information on each of these networks, please check out the `docs` folder.
        
        ## Running the tests
        
        To run the unit tests, you can run the following.
        
        ```bash
        python -m unittest discover tests
        ```
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python :: 3.6
