spark.nn.interfaces.input.poisson

Classes

PoissonSpikerConfig	PoissonSpiker model configuration class.
PoissonSpiker	Transforms a continuous signal to a spiking signal.

Module Contents

class spark.nn.interfaces.input.poisson.PoissonSpikerConfig(__skip_validation__=False, **kwargs)

Bases: spark.nn.interfaces.input.base.InputInterfaceConfig

PoissonSpiker model configuration class.

Parameters:

__skip_validation__ (bool)

max_freq: float

class spark.nn.interfaces.input.poisson.PoissonSpiker(config=None, **kwargs)

Bases: spark.nn.interfaces.input.base.InputInterface

Transforms a continuous signal to a spiking signal. This transformation assumes a very simple poisson neuron model without any type of adaptation or plasticity.

Init:

max_freq: float [Hz]

Input:

signal: FloatArray

Output:

spikes: SpikeArray

Parameters:

config (PoissonSpikerConfig | None)

config: PoissonSpikerConfig

max_freq

build(input_specs)

Build method.

Parameters:

input_specs (dict[str, spark.core.specs.PortSpecs])

Return type:

None

__call__(signal)

Input interface operation.

Input:

A FloatArray of values in the range [0,1].

Output:

A SpikeArray of the same shape as the input.

Parameters:

signal (spark.core.payloads.FloatArray)

Return type:

spark.nn.interfaces.input.base.InputInterfaceOutput