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Recently, driven by the boom of learning neural models, SN P systems have become a rapidly emerging research front. Consequently, many different variants of the learning models of SN P system prevail among the new research results. Although large proprietary deep learning models are still based on the continuous neural network paradigm, spiking neurons are attractive because of their low-energy demands. The purpose of this paper is to provide an up-to-date overview of learning paradigms and techniques for SN P systems. After a brief introduction of the structure and function of SN P systems, we summarise recent approaches to learning and adaptation in SN P systems, including Hebbian learning, Widrow-Hoff algorithm, fuzzy approaches, nonlinear SN P systems, gated and long short-term memory inspired SN P systems, convolutional SN P systems, and more.<\/jats:p>","DOI":"10.1007\/s11047-025-10026-9","type":"journal-article","created":{"date-parts":[[2025,7,10]],"date-time":"2025-07-10T09:13:44Z","timestamp":1752138824000},"page":"665-677","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["A survey on learning models of spiking neural membrane systems"],"prefix":"10.1007","volume":"24","author":[{"given":"Petr","family":"Sos\u00edk","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prithwineel","family":"Paul","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lucie","family":"Ciencialov\u00e1","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,7,8]]},"reference":[{"key":"10026_CR1","doi-asserted-by":"crossref","first-page":"119916","DOI":"10.1016\/j.ins.2023.119916","volume":"656","author":"X Bai","year":"2024","unstructured":"Bai X, Huang Y, Peng H et al (2024) Sequence recommendation using multi-level self-attention network with gated spiking neural P systems. 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