✦ LIBER ✦

A Time-Varying Opportunistic Approach to Lifetime Maximization of Wireless Sensor Networks

✍ Scribed by Cohen, K.; Leshem, A.

Book ID: 119823584
Publisher: IEEE
Year: 2010
Tongue: English
Weight: 484 KB
Volume: 58
Category: Article
ISSN: 1053-587X
DOI: 10.1109/tsp.2010.2052459

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Revenue Maximization in Time-Varying Mul

Revenue Maximization in Time-Varying Multi-Hop Wireless Networks: A Dynamic Pricing Approach

✍ Song, Yang; Zhang, Chi; Fang, Yuguang; Lin, Phone 📂 Article 📅 2012 🏛 IEEE 🌐 English ⚖ 420 KB

Hybrid Genetic Algorithm Using a Forward

Hybrid Genetic Algorithm Using a Forward Encoding Scheme for Lifetime Maximization of Wireless Sensor Networks

✍ Xiao-Min Hu; Jun Zhang; Yan Yu; Chung, H.S.-H.; Yuan-Long Li; Yu-Hui Shi; Xiao-N 📂 Article 📅 2010 🏛 IEEE 🌐 English ⚖ 969 KB

A population based approach to model the

A population based approach to model the lifetime and energy distribution in battery constrained wireless sensor networks

✍ Ramachandran, K.; Sikdar, B. 📂 Article 📅 2010 🏛 IEEE 🌐 English ⚖ 435 KB

A continuum theory-based approach to the

A continuum theory-based approach to the modeling of dynamic wireless sensor networks

✍ Papavassiliou, S.; Zhu, J. 📂 Article 📅 2005 🏛 IEEE 🌐 English ⚖ 585 KB

A new approach to stability analysis of

A new approach to stability analysis of discrete-time recurrent neural networks with time-varying delay

✍ Chunwei Song; Huijun Gao; Wei Xing Zheng 📂 Article 📅 2009 🏛 Elsevier Science 🌐 English ⚖ 178 KB

A new approach to exponential stability

A new approach to exponential stability analysis of neural networks with time-varying delays

✍ Shengyuan Xu; James Lam 📂 Article 📅 2006 🏛 Elsevier Science 🌐 English ⚖ 143 KB

This paper considers the problem of exponential stability analysis of neural networks with time-varying delays. The activation functions are assumed to be globally Lipschitz continuous. A linear matrix inequality (LMI) approach is developed to derive sufficient conditions ensuring the delayed neural