Szczegóły publikacji
Opis bibliograficzny
Bandlimited signal reconstruction from leaky integrate-and-fire encoding using POCS / Nguyen T. Thao, Dominik RZEPKA, Marek MIŚKOWICZ // IEEE Transactions on Signal Processing ; ISSN 1053-587X. — 2023 — vol. 71, s. 1464-1479. — Bibliogr. s. 1479, Abstr. — Publikacja dostępna online od: 2023-03-13
Autorzy (3)
- Thao Nguyen T.
- AGHRzepka Dominik
- AGHMiśkowicz Marek
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 148414 |
|---|---|
| Data dodania do BaDAP | 2023-09-20 |
| Tekst źródłowy | URL |
| DOI | 10.1109/TSP.2023.3256269 |
| Rok publikacji | 2023 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | IEEE Transactions on Signal Processing |
Abstract
Leaky integrate-and-fire (LIF) encoding is a model of neuron transfer function in biology that has recently attracted the attention of the signal processing and neuromorphic computing communities as a technique of event-based sampling for data acquisition. While LIF enables the implementation of analog-circuit signal samplers of lower complexity and higher accuracy simultaneously, the core difficulty of this technique is the retrieval of an input from its LIF-encoded output. In this article, we study this problem in the context of bandlimited inputs, by extracting the most abstract features of an LIF encoder as a generalized nonuniform sampler. In this view, the LIF output is seen as the transformation of the input by a known linear operator. We show that the signal reconstruction method of projection onto convex sets (POCS) converges to a weighted pseudo-inverse of this operator. This allows perfect recovery under uniqueness of reconstruction, minimum-norm reconstruction under incomplete sampling, as well as a noise shaping of time quantization that outperforms standard pseudo-inversion. On the practical side, a single iteration of the POCS method can be used to improve any estimate whose LIF samples are not consistent with those of the input, and a rigorous discrete-time implementation of this iteration is proposed that does not require a Nyquist-rate representation of the signals.
