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The workflow is summarized in five steps. Dataset acquisition and signal encoding (A) with analysis of information content and reconstruction loss (B). Different non-spiking classifiers are identified and employed to produce references for the proposed Recurrent Spiking Neural Network (RSNN) (C), with the latter undergoing a hyperparameter optimization (D). Finally, performances are evaluated, accounting for different metrics and hardware implementations (E).
