Independence Saturation and Strong Independent Saturation in Probabilistic Neural Networks
New Mathematics and Natural Computation, vol.21, no.1, pp.213-227, 2025 (ESCI, Scopus)
- Publication Type: Article / Article
- Volume: 21 Issue: 1
- Publication Date: 2025
- Doi Number: 10.1142/s1793005725500127
- Journal Name: New Mathematics and Natural Computation
- Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Metadex, zbMATH, Civil Engineering Abstracts
- Page Numbers: pp.213-227
- Keywords: Independence, domination, strong domination, independence saturation, strong independent saturation, probabilistic neural networks, network design and communication
- Dokuz Eylül University Affiliated: Yes
Abstract
The independence saturation number IS(G) of a graph G = (V,E) is defined as min{IS(v): v V}, where IS(v) is the maximum cardinality of an independent set that contains v. The strong independent saturation number Is(G) of a graph G = (V,E) is defined as min{Is(v): v ∈ V}, where Is(v) is the maximum cardinality of a minimal strong independent dominating set of G that contains v. This paper is devoted to the computation of independence saturation and strong independent saturation numbers of 3- and 4-layered probabilistic neural networks.