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 …
Fuzzy Petri nets and industrial applications: a review
Fuzzy Petri net (FPN) provides an extremely competent basis for the implementation of
computing reasoning processes and the modeling of systems with uncertainty. This paper …
computing reasoning processes and the modeling of systems with uncertainty. This paper …
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 …
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 …
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 …
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 …
Spiking neural P systems with inhibitory rules
Motivated by the mechanism of inhibitory synapses, a new kind of spiking neural P (SNP)
system rules, called inhibitory rules, is introduced in this paper. Based on this, a new variant …
system rules, called inhibitory rules, is introduced in this paper. Based on this, a new variant …
A time series forecasting approach based on nonlinear spiking neural systems
L Long, Q Liu, H Peng, Q Yang, X Luo… - … Journal of Neural …, 2022 - World Scientific
Nonlinear spiking neural P (NSNP) systems are a recently developed theoretical model,
which is abstracted by nonlinear spiking mechanism of biological neurons. NSNP systems …
which is abstracted by nonlinear spiking mechanism of biological neurons. NSNP systems …
Nonlinear spiking neural P systems
This paper proposes a new variant of spiking neural P systems (in short, SNP systems),
nonlinear spiking neural P systems (in short, NSNP systems). In NSNP systems, the state of …
nonlinear spiking neural P systems (in short, NSNP systems). In NSNP systems, the state of …
Dynamic threshold neural P systems
Pulse coupled neural networks (PCNN, for short) are models abstracting the synchronization
behavior observed experimentally for the cortical neurons in the visual cortex of a cat's brain …
behavior observed experimentally for the cortical neurons in the visual cortex of a cat's brain …