Fuzzy causal networks: general model, inference, and convergence

Authors:
Sanming Zhou;Zhi-Qiang Liu;Jian Ying Zhang
Affiliations:
Dept. of Math. & Stat., Univ. of Melbourne, Vic., Australia;-;-
Venue:
IEEE Transactions on Fuzzy Systems
Year:
2006

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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 in 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.