neural networks as a general-purpose computational framework
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.
To run a sample network, you can run the module.
python -m neuralkernel
The networks currently implemented are:
- Inverting Memory
- Non-Inverting Memory
- Full Subtractor
For more information on each of these networks, please check out the
Running the tests
To run the unit tests, you can run the following.