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Fuzzy causal networks: general model, inference, and convergence

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3 Author(s)
Sanming Zhou ; Dept. of Math. & Stat., Univ. of Melbourne, Vic., Australia ; Zhi-Qiang Liu ; Jian Ying Zhang

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.

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Fuzzy Systems, IEEE Transactions on  (Volume:14 ,  Issue: 3 )