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On the Sampling Sparsity of Neuromorphic Analog-to-Spike Conversion based on Leaky Integrate-and-Fire

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arxiv 2410.17441 v1 pith:2OH5PU5L submitted 2024-10-22 eess.SP cs.NE

Bernhard A.Moser , Michael Lunglmayr This is my paper · ORCID
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keywords analog-to-spikeconversionintegrate-and-fireleakyneuromorphicsensingsparsityalexiewicz
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In contrast to the traditional principle of periodic sensing neuromorphic engineering pursues a paradigm shift towards bio-inspired event-based sensing, where events are primarily triggered by a change in the perceived stimulus. We show in a rigorous mathematical way that information encoding by means of Threshold-Based Representation based on either Leaky Integrate-and-Fire (LIF) or Send-on-Delta (SOD) is linked to an analog-to-spike conversion that guarantees maximum sparsity while satisfying an approximation condition based on the Alexiewicz norm.

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  1. Integrate-and-Fire from a Mathematical and Signal Processing Perspective

    eess.SP 2025-01 reject novelty 5.0 of 10

    Integrate-and-fire with reset-to-mod is shown to be the integral version of send-on-delta sampling, with error bounds, sparsity, and sparse regularization expressed in the Alexiewicz norm.

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