Anomalous Random Neural Networks: a Special Renewal Process

Fuente: arXiv
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Autori principali: Zhang, Hong, Li, Guohua
Natura: Preprint
Pubblicazione: 2024
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author Zhang, Hong
Li, Guohua
author_facet Zhang, Hong
Li, Guohua
contents In this paper we propose an open anomalous semi-Markovian random neural networks model with negative and positive signals with arbitrary random waiting times. We investigate the signal flow process in the anomalous random neural networks based on renewal process, and obtain the corresponding master equation for time evolution of the probability of the potential of the neurons. As examples, we discuss the special cases of exponential waiting times and power law ones, and find the fractional memory effect of the probability of the system state on its history evolution. Besides, the closed random neural networks model is introduced and the corresponding rate equation is given.
format Preprint
id arxiv_https___arxiv_org_abs_2406_18877
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Anomalous Random Neural Networks: a Special Renewal Process
Zhang, Hong
Li, Guohua
Disordered Systems and Neural Networks
In this paper we propose an open anomalous semi-Markovian random neural networks model with negative and positive signals with arbitrary random waiting times. We investigate the signal flow process in the anomalous random neural networks based on renewal process, and obtain the corresponding master equation for time evolution of the probability of the potential of the neurons. As examples, we discuss the special cases of exponential waiting times and power law ones, and find the fractional memory effect of the probability of the system state on its history evolution. Besides, the closed random neural networks model is introduced and the corresponding rate equation is given.
title Anomalous Random Neural Networks: a Special Renewal Process
topic Disordered Systems and Neural Networks
url https://arxiv.org/abs/2406.18877