https://github.com/akshaybabloo/spikes
A Spiking Neural Network encoder for time series data
https://github.com/akshaybabloo/spikes
machine-learning neural-networks spike-encoders spiking-neural-networks
Last synced: about 1 year ago
JSON representation
A Spiking Neural Network encoder for time series data
- Host: GitHub
- URL: https://github.com/akshaybabloo/spikes
- Owner: akshaybabloo
- License: other
- Created: 2016-10-05T06:09:34.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2021-09-05T02:52:58.000Z (almost 5 years ago)
- Last Synced: 2025-06-01T16:21:35.443Z (about 1 year ago)
- Topics: machine-learning, neural-networks, spike-encoders, spiking-neural-networks
- Language: Python
- Homepage: https://akshaybabloo.github.io/Spikes/
- Size: 1.01 MB
- Stars: 21
- Watchers: 3
- Forks: 11
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
Awesome Lists containing this project
README
# Spike Encoders
| Branch | Codecov | CI |
|--------|---------|---------------------------------------------------------------------------------------------------------------------------------------|
| Master | Soon.. |  |
Spike encoders for Spiking Neural Network.
This package consists of two types of spike encoders for spatio-temporal data:
1. Threshold Based Representation (TBR) encoder
2. Bens Spiker Algorithm (BSA) encoder
- [Data](#data)
- [Instillation](#instillation)
- [Example](#example)
- [Contribution](#contribution)
- [Issues](#issues)
## Data
The data given to the encoders are spatio-temporal. Each sample is one `csv` file. In each file, every column is a feature and the rows are time points.
For example each file given in the [Data](https://github.com/akshaybabloo/Spikes/tree/master/Data) folder had 128 rows and 14 columns, 14 columns are the features and 128 columns are the data points.
## Instillation
```
pip install pyspikes
```
## Example
```python
from spikes import encoder
from spikes.utility import ReadCSV
data = ReadCSV('Data').get_samples()['samples']
bsa = encoder.BSA(data)
print(bsa.get_spikes())
tbr = encoder.TBR(data)
print(tbr.get_spikes())
```
## Contribution
All contributions are welcome.
## Issues
Issues can be opened through Github's [Issues](https://github.com/akshaybabloo/Spikes/issues) tab.