Fuzzy causal networks: General model, inference, and convergence

Abstract

In this paper, we first propose a general framework for fuzzy causal networks (FCNs). Then, we study the dynamics and convergence of such general FCNs. We prove that any general FCN with constant weight matrix converges to a limit cycle or a static state, or the trajectory of the FCN is not repetitive. We also prove that under certain conditions a discrete state general FCN converges to its limit cycle or static state n O(n) steps, where n is the number of vertices of the FCN. This is in striking contrast with the exponential running time 2n, which is accepted widely for classic FCNs. © 2006 IEEE.