基于小波包分解和FK分析的次声信号参数估计

频率波数分析法是一种估计信号慢度和方位角的台阵数据处理方法,在地震波信号处理中得到广泛应用,但将频率波数分析法应用于次声信号的时候,分辨率不高,易受噪声的影响,伪峰较明显。因此,本文提出了一种基于小波包分解和FK分析的次声信号参数估计方法,该方法借助小波包分解对信号整个频带的分辨能力,有效提高了算法的分辨率,降低了噪声的影响,有效压制了伪峰,并利用高斯调制正弦信号模拟次声信号,对比分析了方位角的均值、方差和均方根误差,验证了算法的性能,最后利用IS45台站接收的实际次声数据对算法进行对比分析,进一步验证了算法的有效性。     

基于NS2的移动Ad hoc网络典型网络协议比较

无线 Ad hoc网络作为一种典型的自组织网络，其路由协议一直是其实际应用研究的重点。 文章详细的介绍了移动ad hoc网络的三种典型的网络协议DSDV，AODV和DSR。对于网络路由协议的仿真，本文应用了基于Unix平台的免费的网络仿真软件NS2，并详细的分析了仿真场景的生成，源代码的应用，以及仿真脚本的分析。给出了三种典型的ad hoc协议在NS2的仿真条件下的分组投递率的比较，提供了比较结果。结果表明，在本文所建立的移动场景下，按需路由协议比表驱动协议的分组投递率较高。     

Data Rate Aware Reliable Transmission Mechanism in Wireless Sensor Networks using Bayesian Regularized Neural Network approach

Wireless Sensor Networks consists of interconnected nodes that exchange information wirelessly enabling its deployment in innovative application areas. Network reliability streamline this exchange of information and communication technology to improve the overall performance of the network. The network reliability is categorized as: node reliability and link reliability. In this article, the node reliability is quantified with the help of packet reliability. The packet reliability is enhanced by optimizing the data rate using Bayesian Regularized Neural Network approach, which thus makes the network more reliable and sustainable. The optimization is carried out in three phases: network designing, data rate prediction and reliability evaluation. The network design includes the deployment of sensor nodes for gathering the communication data using NS-2.35. In the next phase, data rate prediction is carried out to enhance the reliability of the network. The reliability of a network is directly influenced by the packet loss ratio. According to research and the network experts, the acceptable threshold limit for the packet loss ratio is 5 percent. The data rate prediction is carried out to minimize the packet loss using the Bayesian Regularized Neural Network algorithm. The packet reliability is measured in terms of packet loss across the wireless network. Finally, a novel framework is presented for evaluating the packet reliability of the wireless network.