norse.torch.functional

norse.torch.functional#

Stateless spiking neural network components.

Modules

`adjoint`	Adjoint-based neuron activation functions and optimization code.
`coba_lif`
`correlation_sensor`
`decode`	Stateless decoding functionality for Norse, where events in time are converted to numerical representations.
`encode`	Stateless encoding functionality for Norse, offering different ways to convert numerical inputs to the spiking domain.
`filter`	An Exponential smoothing or exponential filter that smoothing time series data using the exponential window function.
`heaviside`	A heaviside step function that truncates numbers <= 0 to 0 and everything else to 1.
`iaf`
`izhikevich`
`leaky_integrator`	Leaky integrators describe a leaky neuron membrane that integrates incoming currents over time, but never spikes.
`leaky_integrator_box`	Leaky integrators describe a leaky neuron membrane that integrates incoming currents over time, but never spikes.
`lif`	A popular neuron model that combines a `norse.torch.functional.leaky_integrator` with spike thresholds to produce events (spikes).
`lif_adex`
`lif_adex_refrac`
`lif_box`	A simplified version of the popular leaky integrate-and-fire neuron model that combines a `norse.torch.functional.leaky_integrator` with spike thresholds to produce events (spikes).
`lif_correlation`
`lif_ex`
`lif_mc`
`lif_mc_refrac`
`lif_refrac`
`lift`	A module for lifting neuron activation functions in time. Simlar to the :module:`.lift`_ module.
`logical`
`lsnn`	Long-short term memory module, building on the work by [G.
`receptive_field`	A module for creating receptive fields.
`regularization`	This module contains functional components for regularization operations on spiking layers, where it can be desirable to regularize spikes, membrane parameters, or other properties over time.
`reset`	Functions for reset mechanisms.
`spikes_to_times_decoder`
`stdp`
`stdp_sensor`
`superspike`
`test`
`threshold`
`tsodyks_makram`