Predictive-Coding-Inspired Reconstruction of Nonlinear Dynamics in Spiking Neural Networks
Accurate reconstruction of nonlinear time-dependent dynamics is a fundamental challenge for recurrent spiking neural networks and neuromorphic signal-processing systems. In this work, we compare two prediction-error architectures for nonlinear state reconstruction: a model with an external comparator and a model employ...