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 …

Spiking neural P systems (abbreviated as SNP systems) are models of computation that
mimic the behavior of biological neurons. The spiking neural P systems with communication …

In recent years, incremental sampling-based motion planning algorithms have been widely
used to solve robot motion planning problems in high-dimensional configuration spaces. In …

Asynchronous spiking neural P (AsynSN P) systems are a class of distributed and parallel
computational models working in a non-synchronized mode, inspired by the mechanism of …

Spiking neural P systems (SN P systems) are a class of distributed and parallel computation
models, which are inspired by the way in which neurons process information by means of …

Spiking neural (SN) P systems inspired from biological neural network are not only a kind of
distributed and parallel membrane computing model, but also a new third-generation neural …

Spiking neural P systems (SNP systems) are a class of distributed and parallel computation
models, which are inspired by the way in which neurons process information through spikes …

This paper proposes a bio-inspired learning approach, fault diagnosis method based on
learning spiking neural P system with belief AdaBoost, for oil-immersed power transformer …

At present, all known spiking neural P systems (SN P systems) are established by manual
design rather than automatic design. The method of manual design poses two problems …

Maximally parallel manner is a usual rule application strategy for P systems, where rules
should be used in parallel to the maximum degree possible. In this work, we consider a rule …