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A survey of nature-inspired computing: Membrane computing
Nature-inspired computing is a type of human-designed computing motivated by nature,
which is based on the employ of paradigms, mechanisms, and principles underlying natural …
which is based on the employ of paradigms, mechanisms, and principles underlying natural …
Membrane computing and image processing: a short survey
Membrane computing is a well-known research area in computer science inspired by the
organization and behavior of live cells and tissues. Their computational devices, called P …
organization and behavior of live cells and tissues. Their computational devices, called P …
An attention-aware long short-term memory-like spiking neural model for sentiment analysis
LSTM-SNP model is a recently developed long short-term memory (LSTM) network, which is
inspired from the mechanisms of spiking neural P (SNP) systems. In this paper, LSTM-SNP …
inspired from the mechanisms of spiking neural P (SNP) systems. In this paper, LSTM-SNP …
Gated spiking neural P systems for time series forecasting
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 …
A hybrid feature model and deep-learning-based bearing fault diagnosis
Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary
machines. It can reduce economical losses by eliminating unexpected downtime in industry …
machines. It can reduce economical losses by eliminating unexpected downtime in industry …
Attention-enabled gated spiking neural P model for aspect-level sentiment classification
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 …
Edge detection method based on nonlinear spiking neural systems
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 …
Medical image fusion method based on coupled neural P systems in nonsubsampled shearlet transform domain
Coupled neural P (CNP) systems are a recently developed Turing-universal, distributed and
parallel computing model, combining the spiking and coupled mechanisms of neurons. This …
parallel computing model, combining the spiking and coupled mechanisms of neurons. This …
A weighted corrective fuzzy reasoning spiking neural P system for fault diagnosis in power systems with variable topologies
This paper focuses on power system fault diagnosis based on Weighted Corrective Fuzzy
Reasoning Spiking Neural P Systems with real numbers (rWCFRSNPSs) to propose a …
Reasoning Spiking Neural P Systems with real numbers (rWCFRSNPSs) to propose a …
A rough set-based bio-inspired fault diagnosis method for electrical substations
Imprecision and uncertainty in the alarm messages may significantly affect the accuracy and
reliability of substation fault diagnosis results. To deal with that, a new rough set-based bio …
reliability of substation fault diagnosis results. To deal with that, a new rough set-based bio …