摘要
为提高弱稀疏性条件下基于压缩感知的无线传感器网络事件检测的可靠性和有效性,提出一种迭代凸优化网络事件检测算法。该方法利用多次凸优化算法共同对弱稀疏性网络事件进行检测,在每次运行凸优化算法后,对已检测出的网络事件进行加权以降低权值,从而有利于其他网络事件在下次凸优化中得到检测。与以往的无线传感器网络事件检测算法相比,迭代凸优化检测算法可在网络事件稀疏性较弱的情况下保证成功检测概率。仿真实验验证了所提算法的正确性。
In order to improve the reliability and effectiveness of event detection for wireless sensor networks （WSN） with weak sparsity based on compressed sensing （CS）, an iterative convex optimization network event detection algorithm is proposed. The method detects events for networks with weak sparsity by multiple convex optimizations algorithm. Once a convex optimization algorithm finishes running, the detected network event is down-weighted so that other network events can be detected during the next convex optimization. Compared with previous wireless sensor network event detection algorithms, the iterative convex optimization detection algorithm can ensure the probability of successful detection for network events with weak sparsity. Simulation experiments validate the proposed algorithm.
出处
《计算机应用与软件》
CSCD
北大核心
2014年第3期104-107,共4页
Computer Applications and Software
基金
江苏省科技计划项目(BE2011376)
关键词
无线传感器网络
压缩感知
事件检测
迭代凸优化
Wireless sensor network （WSN） Compressed sensing Event detection Iterative convex optimization
