Global exponential stability results for the host‐parasitoid model of sugarcane borer in stochastic environment with impulsive effects via non‐fragile control: An LMI approach

2021 ◽  
Author(s):  
Dianavinnarasi Joseph ◽  
Raja Ramachandran ◽  
Jehad Alzabut ◽  
Jinde Cao ◽  
Michal Niezabitowski ◽  
...  
Keyword(s):  
Exponential Stability ◽  
Global Exponential Stability ◽  
Impulsive Effects ◽  
Stochastic Environment ◽  
Lmi Approach ◽  
Sugarcane Borer ◽  
Stability Results

scholarly journals Switching Signal Design for Global Exponential Stability of Uncertain Switched Neutral Systems

2009 ◽  
Vol 2009 ◽  
pp. 1-17 ◽  
Author(s):  
Ker-Wei Yu
Keyword(s):  
Exponential Stability ◽  
Global Exponential Stability ◽  
Signal Design ◽  
Neutral Systems ◽  
Numerical Examples ◽  
Switching Signal ◽  
The Stability ◽  
Switched Neutral Systems ◽  
Delay Dependent ◽  
Stability Results

The switching signal design for global exponential stability of switched neutral systems is investigated in this paper. LMI-based delay-dependent and delay-independent criteria are proposed to guarantee the global stability via the constructed switching signal. Razumikhin-like approach is used to find the stability results. Finally, some numerical examples are illustrated to show the main results.

STABILITY ANALYSIS OF IMPULSIVE COHEN-GROSSBERG NEURAL NETWORK WITH UNBOUNDED DISCRETE TIME-VARYING DELAYS

2007 ◽  
Vol 17 (05) ◽  
pp. 407-417 ◽  
Author(s):  
QIANKUN SONG ◽  
JINDE CAO
Keyword(s):  
Neural Network ◽  
Stability Analysis ◽  
Exponential Stability ◽  
Discrete Time ◽  
Global Exponential Stability ◽  
Sufficient Conditions ◽  
Time Varying ◽  
Analysis Method ◽  
Inequality Technique ◽  
Stability Results

In this paper, the impulsive Cohen-Grossberg neural network with unbounded discrete time-varying delays is considered. By using the analysis method and inequality technique, several sufficient conditions are obtained to ensure the global exponential stability of the addressed neural network. These results generalize the existing relevant stability results. Two examples with simulations are given to show the effectiveness of the obtained results.

scholarly journals Global exponential stability of Clifford-valued neural networks with time-varying delays and impulsive effects

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
G. Rajchakit ◽  
R. Sriraman ◽  
N. Boonsatit ◽  
P. Hammachukiattikul ◽  
C. P. Lim ◽  
...  
Keyword(s):  
Exponential Stability ◽  
Global Exponential Stability ◽  
Sufficient Conditions ◽  
Impulsive Effects ◽  
Linear Matrix ◽  
Time Varying ◽  
Special Cases ◽  
Inequality Techniques ◽  
Complex Valued ◽  
Clifford Numbers

AbstractIn this study, we investigate the global exponential stability of Clifford-valued neural network (NN) models with impulsive effects and time-varying delays. By taking impulsive effects into consideration, we firstly establish a Clifford-valued NN model with time-varying delays. The considered model encompasses real-valued, complex-valued, and quaternion-valued NNs as special cases. In order to avoid the issue of non-commutativity of the multiplication of Clifford numbers, we divide the original n-dimensional Clifford-valued model into $2^{m}n$ 2 m n -dimensional real-valued models. Then we adopt the Lyapunov–Krasovskii functional and linear matrix inequality techniques to formulate new sufficient conditions pertaining to the global exponential stability of the considered NN model. Through numerical simulation, we show the applicability of the results, along with the associated analysis and discussion.

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