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.
Getting Started
To run a sample network, you can run the module.
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.
pytest
1 maintainer
Metadata
1 maintainer
Release files for neuralkernel 0.0.8
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| neuralkernel-0.0.8-py3-none-any.whl | Python 3 | none | any | Details |
Release files / neuralkernel-0.0.8-py3-none-any.whl
| Download URL | neuralkernel-0.0.8-py3-none-any.whl |
|---|---|
| Size | 8.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
b9ad5a617731d9d425c8009d24a61bd2f72247084624e10db8ea42a4f4ebedf1
|
|
BLAKE2b-256 checksum How to use checksums |
901510514f67a7351ff31cb93c08e5a415393e12d4e419d1aa1f1500c12f4820
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/38.4.0 requests-toolbelt/0.8.0 tqdm/4.19.8 CPython/3.6.6
|
Security for neuralkernel 0.0.8
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
