Title :
Nonparametric decentralized detection using kernel methods
Author :
Nguyen, XuanLong ; Wainwright, Martin J. ; Jordan, Michael I.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., Univ. of California, Berkeley, CA, USA
Abstract :
We consider the problem of decentralized detection under constraints on the number of bits that can be transmitted by each sensor. In contrast to most previous work, in which the joint distribution of sensor observations is assumed to be known, we address the problem when only a set of empirical samples is available. We propose a novel algorithm using the framework of empirical risk minimization and marginalized kernels and analyze its computational and statistical properties both theoretically and empirically. We provide an efficient implementation of the algorithm and demonstrate its performance on both simulated and real data sets.
Keywords :
distributed sensors; nonparametric statistics; signal detection; empirical risk minimization; kernel method; marginalized kernel; nonparametric decentralized detection; statistical property; Algorithm design and analysis; Computational modeling; Decision making; Kernel; Power measurement; Relays; Risk analysis; Risk management; Sensor fusion; Sensor systems; Decentralized detection; kernel methods; nonparametric; statistical ML;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2005.857020