Frequency-locked resonate-and-fire neurons are recast as a complex state-space model with phase outputs, enabling FFT-based parallel training and a new bridge to hyperdimensional computing, subject to a derivation gap.
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Phase State Space Models: Parallel, Surrogate-Free Training of Spiking Networks
Frequency-locked resonate-and-fire neurons are recast as a complex state-space model with phase outputs, enabling FFT-based parallel training and a new bridge to hyperdimensional computing, subject to a derivation gap.