An overview of hardware implementation of membrane computing models
The model of membrane computing, also known under the name of P systems, is a bio-
inspired large-scale parallel computing paradigm having a good potential for the design of …
inspired large-scale parallel computing paradigm having a good potential for the design of …
A bibliometric analysis of membrane computing (1998–2019)
H Rong, Y Duan, G Zhang - Journal of Membrane Computing, 2022 - Springer
Membrane computing as a topic in the Mathematics Subjects Classification 2020 by
Mathematical Reviews and zbMATH is a sign of maturity of this research area initiated in the …
Mathematical Reviews and zbMATH is a sign of maturity of this research area initiated in the …
A layered spiking neural system for classification problems
Biological brains have a natural capacity for resolving certain classification tasks. Studies on
biologically plausible spiking neurons, architectures and mechanisms of artificial neural …
biologically plausible spiking neurons, architectures and mechanisms of artificial neural …
Hyperspectral image unsupervised classification by robust manifold matrix factorization
Hyperspectral remote sensing image unsupervised classification, which assigns each pixel
of the image into a certain land-cover class without any training samples, plays an important …
of the image into a certain land-cover class without any training samples, plays an important …
A novel machine learning model for estimation of sale prices of real estate units
Predicting the price of housing is of paramount importance for near-term economic
forecasting of any nation. This paper presents a novel and comprehensive model for …
forecasting of any nation. This paper presents a novel and comprehensive model for …
Attention-enabled gated spiking neural P model for aspect-level sentiment classification
Y Huang, H Peng, Q Liu, Q Yang, J Wang… - Neural Networks, 2023 - Elsevier
Gated spiking neural P (GSNP) model is a recently developed recurrent-like network, which
is abstracted by nonlinear spiking mechanism of nonlinear spiking neural P systems. In this …
is abstracted by nonlinear spiking mechanism of nonlinear spiking neural P systems. In this …
Fault diagnosis of electric power systems based on fuzzy reasoning spiking neural P systems
This paper proposes a graphic modeling approach, fault diagnosis method based on fuzzy
reasoning spiking neural P systems (FDSNP), for power transmission networks. In FDSNP …
reasoning spiking neural P systems (FDSNP), for power transmission networks. In FDSNP …
Edge detection method based on nonlinear spiking neural systems
R Xian, R Lugu, H Peng, Q Yang, X Luo… - International journal of …, 2023 - World Scientific
Nonlinear spiking neural P (NSNP) systems are a class of neural-like computational models
inspired from the nonlinear mechanism of spiking neurons. NSNP systems have a …
inspired from the nonlinear mechanism of spiking neurons. NSNP systems have a …
Gated spiking neural P systems for time series forecasting
Q Liu, L Long, H Peng, J Wang, Q Yang… - … on Neural Networks …, 2021 - ieeexplore.ieee.org
Spiking neural P (SNP) systems are a class of neural-like computing models, abstracted by
the mechanism of spiking neurons. This article proposes a new variant of SNP systems …
the mechanism of spiking neurons. This article proposes a new variant of SNP systems …
Spiking Neural P Systems with Communication on Request
Spiking Neural P Systems are Neural System models characterized by the fact that each
neuron mimics a biological cell and the communication between neurons is based on …
neuron mimics a biological cell and the communication between neurons is based on …