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1.2.1
GETTING STARTED
Installation
Fundamentals of Sinabs
A quick (and over-simplified) introduction to spiking neurons
Quickstart Sinabs
Python versions, pyenv and pipenv
SINABS GALLERY
Neuron models
Exponential Leaky Layer (ExpLeak)
Adaptive Leaky Integrate and Fire (ALIF)
Integrate and Fire (IAF)
Leaky Integrate and Fire (LIF)
Spike functions
MultiSpike
SingleSpike
MaxSpike
Surrogate gradient functions
Gaussian
Heaviside
MultiGaussian
SingleExponential
PeriodicExponential
TUTORIALS
Training by backpropagation through time (BPTT)
Converting an ANN to an SNN
Scaling parameters for rate-coded conversion to SNNs
sinabs Tutorial 使用入门
HOW TOS
Training an ANN with fewer synops
Training an SNN with fewer synops
Change activations in spiking layers
PLUGINS
API REFERENCE
network
layers
StatefulLayer
SqueezeMixin
IAF
IAFSqueeze
IAFRecurrent
LIF
LIFSqueeze
LIFRecurrent
ALIF
ALIFRecurrent
ExpLeak
ExpLeakSqueeze
SpikingMaxPooling2dLayer
SumPool2d
Img2SpikeLayer
Sig2SpikeLayer
Cropping2dLayer
Repeat
FlattenTime
UnflattenTime
NeuromorphicReLU
QuantizeLayer
activation
SingleSpike
MultiSpike
MaxSpike
MembraneReset
MembraneSubtract
SingleExponential
PeriodicExponential
Heaviside
Gaussian
MultiGaussian
from_torch
SynOpCounter
utils
ABOUT
About this project
How is Sinabs different?
Contributing to sinabs
Release notes
repository
open issue
suggest edit
.rst
.pdf
Spike functions
Spike functions
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MultiSpike
MultiSpike
SingleSpike
SingleSpike
MaxSpike
MaxSpike
