268 Adaptive Leaky Integrate and Fire Neuron
268 : Adaptive Leaky Integrate and Fire Neuron
- Author: Sydnie Figuerres
- Description: Simulates an adaptive leaky integrate and fire neuron
- GitHub repository
- Clock: 0 Hz
How it works
This neuron model is an adaptive leaky integrate and fire neuron. It behaves similarly to a traditional leaky integrate and fire neuron(LIF), but takes into consideration the frequency of spikes occurring. In other words, if a simple LIF were to spike at a consistent rate, the adaptive LIF model will spike less often over time.
How to test
The file test.py shpuld be used to test this model. By applying varying input values with an expected output, you can measure the accuracy of this implementation of an adaptive leaky integrate and fire neuron.
External hardware
There is no external hardware for this model.
IO
| # | Input | Output | Bidirectional |
|---|---|---|---|
| 0 | Input current bit[0] | State variable bit[0] | |
| 1 | Input current bit[1] | State variable bit[1] | |
| 2 | Input current bit[2] | State variable bit[2] | |
| 3 | Input current bit[3] | State variable bit[3] | |
| 4 | Input current bit[4] | State variable bit[4] | |
| 5 | Input current bit[5] | State variable bit[5] | |
| 6 | Input current bit[6] | State variable bit[6] | |
| 7 | Input current bit[7] | State variable bit[7] | Spike bit |