Cargando…
Universal Nonlinear Spiking Neural P Systems with Delays and Weights on Synapses
The nonlinear spiking neural P systems (NSNP systems) are new types of computation models, in which the state of neurons is represented by real numbers, and nonlinear spiking rules handle the neuron's firing. In this work, in order to improve computing performance, the weights and delays are in...
Autores principales: | Wang, Liping, Liu, Xiyu, Zhao, Yuzhen |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8413071/ https://www.ncbi.nlm.nih.gov/pubmed/34484319 http://dx.doi.org/10.1155/2021/3285719 |
Ejemplares similares
-
Turing Universality of Weighted Spiking Neural P Systems with Anti-spikes
por: Ren, Qianqian, et al.
Publicado: (2020) -
Spiking Neural P Systems with Neuron Division and Dissolution
por: Zhao, Yuzhen, et al.
Publicado: (2016) -
Spiking Neural P Systems with Membrane Potentials, Inhibitory Rules, and Anti-Spikes
por: Liu, Yuping, et al.
Publicado: (2022) -
Spiking Neural Network (SNN) With Memristor Synapses Having Non-linear Weight Update
por: Kim, Taeyoon, et al.
Publicado: (2021) -
Fuzzy Reasoning Numerical Spiking Neural P Systems for Induction Motor Fault Diagnosis
por: Yin, Xiu, et al.
Publicado: (2022)