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Norm_STDP.py

Norm_STDP.py

 
 

Overall_strength_error.py

Overall_strength_error.py

 
 

Readme

Readme

 
 

Spike.py

Spike.py

 
 

Spike_time.py

Spike_time.py

 
 

efficacy_fractional_contribution.py

efficacy_fractional_contribution.py

 
 

feedforword.py

feedforword.py

 
 

main.py

main.py

 
 

parameter_intialized.py

parameter_intialized.py

 
 

potential__accumulation.png

potential__accumulation.png

 
 

predict.py

predict.py

 
 

preprocess.py

preprocess.py

 
 

reciptive_field.py

reciptive_field.py

 
 

train.py

train.py

 
 

update.py

update.py

 
 

weight_intialized.py

weight_intialized.py

 
 

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Run
# python main.py

New Dataset
# Add new dataset from main.

Hyperparameter initialization.
# parameter Edit in parameter_intialized.py file.

Classification
# Works for binary Classification.

Demo
# synthetic dataset with 2 input used For training and tested  Demo. 

Tested on
# Tested on multiple datasets LIVER, Inosphere, WBC, PIMA.

**Reference**
SEFRON: A New Spiking Neuron Model With Time-Varying Synaptic Efficacy Function for Pattern Classification.
Jeyasothy A, Sundaram S, Sundararajan N.

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Spiking Neural network

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spiking-neural-networks spike-time-dependent-plasticity binary-classification spike-trains sefron

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