In:
Mathematical Methods in the Applied Sciences, Wiley, Vol. 42, No. 3 ( 2019-02), p. 982-998
Abstract:
This paper studies the robust partially mode‐dependent H ∞ filtering for nonhomogeneous Markovian jump neural networks with additive gain perturbations. The discrete time‐varying jump transition probability matrix is considered to be a polytope set. A partially mode‐dependent filter with additive gain perturbations is constructed to increase the robustness of the filter, which is subjects to H ∞ performance index. Based on the Lyapunov function approach, sufficient conditions are established such that the filtering error system is robustly stochastically stable. The efficiency of the new technique is illustrated by an illustrative example and a biological network example.
Type of Medium:
Online Resource
ISSN:
0170-4214
,
1099-1476
Language:
English
Publisher:
Wiley
Publication Date:
2019
detail.hit.zdb_id:
1478610-2
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