Wireless sensor networks (WSNs) monitor dynamic environments that change rapidly over
time. This dynamic behavior is either caused by external factors or initiated by the system …

Complementary to the fancy big data applications, networking for big data is an
indispensable supporting platform for these applications in practice. This emerging research …

压缩感知是建立在矩阵分析, 统计概率论, 拓扑几何, 优化与运筹学, 泛函分析等基础上的一种
全新的信息获取与处理的理论框架. 它基于信号的可压缩性, 通过低维空间, 低分辨率, 欠Nyquist …

摘要信息感知作为物联两的基本功能. 是物联网信息“全面感知” 的手段. 信息交互是物联网应用
与服务的基础, 是物联网“物物互联” 的目的. 随着物联网研究热潮的兴起, 以传统无线传感器网络 …

In the past five years, deep learning methods have become state-of-the-art in solving various
inverse problems. Before such approaches can find application in safety-critical fields, a …

The emerging compressed sensing (CS) theory can significantly reduce the number of
sampling points that directly corresponds to the volume of data collected, which means that …

Gossip algorithms are attractive for in-network processing in sensor networks because they
do not require any specialized routing, there is no bottleneck or single point of failure, and …

In recent years, compressed sensing (CS) has attracted considerable attention in areas of
applied mathematics, computer science, and electrical engineering by suggesting that it may …

In this paper, we model the components of the compressive sensing (CS) problem, ie, the
signal acquisition process, the unknown signal coefficients and the model parameters for the …

This paper presents the first complete design to apply compressive sampling theory to
sensor data gathering for large-scale wireless sensor networks. The successful scheme …