A survey of nature-inspired computing: Membrane computing

B Song, K Li, D Orellana-Martín… - ACM Computing …, 2021 - dl.acm.org
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 …

Hyperparameter optimization in learning systems

R Andonie - Journal of Membrane Computing, 2019 - Springer
While the training parameters of machine learning models are adapted during the training
phase, the values of the hyperparameters (or meta-parameters) have to be specified before …

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 …

LSTM-SNP: A long short-term memory model inspired from spiking neural P systems

Q Liu, L Long, Q Yang, H Peng, J Wang… - Knowledge-Based Systems, 2022 - Elsevier
Spiking neural P (SNP) systems are a class of neural-like membrane computing models that
are abstracted by applying the mechanisms of spiking neurons. In SNP systems, each …

Echo spiking neural P systems

L Long, R Lugu, X Xiong, Q Liu, H Peng, J Wang… - Knowledge-Based …, 2022 - Elsevier
Nonlinear spiking neural P (NSNP) systems are distributed parallel neural-like computing
models that abstract the nonlinear spiking mechanisms of biological neurons. Echo state …

An unsupervised segmentation method based on dynamic threshold neural P systems for color images

Y Cai, S Mi, J Yan, H Peng, X Luo, Q Yang, J Wang - Information Sciences, 2022 - Elsevier
Dynamic threshold neural P (DTNP) systems are a new variant of spiking neural P (SNP)
systems, abstracted by the spiking and dynamic threshold mechanisms of biological …

Numerical spiking neural P systems

T Wu, L Pan, Q Yu, KC Tan - IEEE Transactions on Neural …, 2020 - ieeexplore.ieee.org
Spiking neural P (SN P) systems are a class of discrete neuron-inspired computation
models, where information is encoded by the numbers of spikes in neurons and the timing of …

Design of logic gates using spiking neural P systems with homogeneous neurons and astrocytes-like control

T Song, P Zheng, MLD Wong, X Wang - Information Sciences, 2016 - Elsevier
In biological nervous systems, the operation of interacting neurons depends largely on the
regulation from astrocytes. Inspired by this biological phenomenon, spiking neural P …

Spiking neural P systems with scheduled synapses

FGC Cabarle, HN Adorna, M Jiang… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Spiking neural P systems (SN P systems) are models of computation inspired by biological
spiking neurons. SN P systems have neurons as spike processors, which are placed on the …

Multi-focus image fusion based on dynamic threshold neural P systems and surfacelet transform

B Li, H Peng, J Wang, X Huang - Knowledge-Based Systems, 2020 - Elsevier
Dynamic threshold neural P systems (DTNP systems) are recently proposed distributed and
parallel computing models, inspired from the intersecting cortical model. DTNP systems …