Exponential Transient Classes of Symmetric Neural N etworks for Synchronous and Sequential Updating
Éric Goles, Ángel Martínez · Complex Systems · 1989
We exhibit a class of symmetric neural networks which synchronous iteration possesses an exponen tial transient length. In fact if {I , ... , n} is the set of nodes we prove the transient length satisfies T 2: 2 n / 3 . For sequential up dating we get the bound f 2: 2 n / 6 • Thi s behavior shows t hat the dynami cs of these class of network s is complex while the steady states are simple: only fixed points or orbits of period 2.