A survey on learning models of spiking neural membrane systems

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61988987%3A17610%2F25%3AA2603B1L" target="_blank" >RIV/61988987:17610/25:A2603B1L - isvavai.cz</a>
Alternative codes found
RIV/47813059:19240/25:A0001537
Result on the web
<a href="https://link.springer.com/article/10.1007/s11047-025-10026-9" target="_blank" >https://link.springer.com/article/10.1007/s11047-025-10026-9</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s11047-025-10026-9" target="_blank" >10.1007/s11047-025-10026-9</a>

Result language
angličtina
Original language name
A survey on learning models of spiking neural membrane systems
Original language description
Spiking neural P systems (SN P systems) are a mathematical model of neural networks, abstracting the way biological neurons communicate with spikes, developed within the framework of the membrane computing theory. 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.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/EH23_025%2F0008724" target="_blank" >EH23_025/0008724: Biography of Fake News with a Touch of AI: Dangerous Phenomenon through the Prism of Modern Human Sciences</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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