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A Spiking Neural Network encoder for time series data
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:
- Threshold Based Representation (TBR) encoder
- Bens Spiker Algorithm (BSA) encoder
- Data
- Instillation
- Example
- Contribution
- 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 folder had 128 rows and 14 columns, 14 columns are the features and 128 columns are the data points.
Instillation
pip install pyspikes
Example
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 tab.