Time evolution of the extremely diluted Blume-Emery-Griffiths neural network
classification
❄️ cond-mat.stat-mech
cond-mat.dis-nn
keywords
networkretrievalblume-emery-griffithsdilutedevolutionextremelyfluctuationneural
read the original abstract
The time evolution of the extremely diluted Blume-Emery-Griffiths neural network model is studied, and a detailed equilibrium phase diagram is obtained exhibiting pattern retrieval, fluctuation retrieval and self-sustained activity phases. It is shown that saddle-point solutions associated with fluctuation overlaps slow down considerably the flow of the network states towards the retrieval fixed points. A comparison of the performance with other three-state networks is also presented.
This paper has not been read by Pith yet.
discussion (0)
Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.