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Global robust exponential stability problems for Cohen-Grossberg neural networks are investigated in this paper. New sufficient conditions are derived to ensure the global robust exponential stability of the equilibrium point by using a new inequality and linear matrix inequality technique. A numerical example is given to show the effectiveness of the theoretical results.
Multiple Channel Design (MCD) has been adopted widely in wireless networks to increase throughput and reliability with relatively less energy consumption. Due to physical restrictions of sensor nodes, applying multiple radio channels in sensor networks poses significant challenges, particularly on energy consumption. To address such challenges, we propose an energy-aware MCD scheme called SmartChannel...
In this paper, we present a group trust management system S3Trust for collaborative services in peer-to-peer grid systems. S3Trust is based on personalized trust rating and selective aggregation algorithms. Leveraging the robustness of a simplistic but elegant co-constraint aggregation algorithm (inspired by H-index) under incomplete and uncertain circumstances, S3Trust offers a robust and lightweight...
In this paper, several novel sufficient criteria are derived for checking the uniqueness and global robust exponential stability of the equilibrium point for interval Cohen-Grossberg neural networks with time-varying delays. A new approach combing the Lyapunov functional with the matrix inequality techniques is taken to investigate this problem. Also, some remarks and two examples are given to show...
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