An Improved Stability Criterion for Digital Filters With Generalized Overflow Arithmetic and Time-Varying Delay

2020 ◽  
Vol 67 (10) ◽  
pp. 2099-2103 ◽  
Author(s):  
Chuan-Ke Zhang ◽  
Ke-You Xie ◽  
Yong He ◽  
Qing-Guo Wang ◽  
Min Wu
Automatika ◽  
2019 ◽  
Vol 61 (2) ◽  
pp. 229-237
Author(s):  
Wenxi Feng ◽  
Fei Luo ◽  
Wenyong Duan ◽  
Yan Li ◽  
Jian Chen

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Lei Ding ◽  
Hong-Bing Zeng ◽  
Wei Wang ◽  
Fei Yu

This paper investigates the stability of static recurrent neural networks (SRNNs) with a time-varying delay. Based on the complete delay-decomposing approach and quadratic separation framework, a novel Lyapunov-Krasovskii functional is constructed. By employing a reciprocally convex technique to consider the relationship between the time-varying delay and its varying interval, some improved delay-dependent stability conditions are presented in terms of linear matrix inequalities (LMIs). Finally, a numerical example is provided to show the merits and the effectiveness of the proposed methods.


2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Tiejun Li ◽  
Junkang Tian

This paper is concerned with delay-dependent stability for continuous systems with two additive time-varying delay components. By constructing a new class of Lyapunov functional and using a new convex polyhedron method, a new delay-dependent stability criterion is derived in terms of linear matrix inequalities. The obtained stability criterion is less conservative than some existing ones. Finally, numerical examples are given to illustrate the effectiveness of the proposed method.


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