Random graphs in a neural computation model

Document Type

Article

Publication Date

6-1-2003

Abstract

We examine in this work the following graph theory problem that arises in neural computations that involve the learning of boolean expressions by studying the asymptotic connectivity properties of Gn,1/(kn)1/2 random graphs, where k is a fixed positive integer. For an undirected graph G = (V, E) let N(X, Y) = {v ∈ V - (X ∪ Y)| ∃x ∈ X with (v, x) ∈ E}. For fixed k construct an undirected graph G = (V, E) such that for all disjoint sets A, B ⊆ V such that |A| = |B| = k, and C = N(A, B) ∩ N(B, A), set C is such that |C| is either exactly k or as close to k as possible. Asymptotic results for large values of k are also presented.

Identifier

13844306688 (Scopus)

Publication Title

International Journal of Computer Mathematics

External Full Text Location

https://doi.org/10.1080/0020716031000079518

e-ISSN

10290265

ISSN

00207160

First Page

689

Last Page

707

Issue

6

Volume

80

This document is currently not available here.

Share

COinS