FiTS spiking neurons improve auditory task performance over LIF baselines by factorizing computation into frequency selectivity and group-delay-based temporal shaping, yielding interpretable per-neuron parameters.
The heidelberg spiking data sets for the systematic evaluation of spiking neural networks.IEEE Trans
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FiTS: Interpretable Spiking Neurons via Frequency Selectivity and Temporal Shaping
FiTS spiking neurons improve auditory task performance over LIF baselines by factorizing computation into frequency selectivity and group-delay-based temporal shaping, yielding interpretable per-neuron parameters.