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1.0.5
  • 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
    • sinabs Tutorial 使用入门
  • HOW TOS
    • Minimise the number of synaptic operations
    • 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
Theme by the Executable Book Project
  • repository
  • open issue
  • suggest edit
  • .rst

HOW TOS

HOW TOS#

  • Minimise the number of synaptic operations
  • Change activations in spiking layers

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Minimise the number of synaptic operations

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