Sampling design for Gaussian detection problems
Sampling design for Gaussian detection problems
复制标题
高斯检测问题的采样设计
DOI：
10.1109/78.622955
复制
发表时间：
1997
期刊：
影响因子：
--
通讯作者：
P. Varshney
中科院分区：
文献类型：
--
作者：
Chao;P. Varshney
我们提出了一种设计高斯假设检验问题抽样方案的方法。我们的设计方法基于 Ali-Silvey 类（参见 J. Royal Stat. Soc., Series B, vol.28, p.131-43, 1996）距离测量。对于强信号情况下的采样设计问题，获得了类条件密度之间的 Bhattacharyya 距离、I 散度、J 散度和 Chernoff 距离的闭合形式。还导出了适用于弱信号情况下的检测问题的Ali-Silvey距离测量类的新成员。确定采样方案以分别最大化这四个距离测量以及针对强信号情况和弱信号情况的新距离测量。通过数值示例将我们的采样方案的检测性能与其他各种采样方案的检测性能进行比较。比较表明，基于 Ali-Silvey 距离度量的抽样设计具有优越的性能。
We propose an approach for the design of sampling schemes for Gaussian hypothesis testing problems. Our approach for this design is based on the class of Ali-Silvey (see J. Royal Stat. Soc., Series B, vol.28, p.131-43, 1996) distance measures. Closed forms for the Bhattacharyya distance, the I-divergence, the J-divergence, and the Chernoff distance between the class conditional densities are obtained for the sampling design problem in the strong signal case. A new member of the class of Ali-Silvey distance measures that is suitable for the detection problem in the weak signal case is also derived. Sampling schemes are determined to maximize those four distance measures as well as the new distance measure for the strong signal case and the weak signal case, respectively. The detection performance of our sampling schemes is compared with those of various other sampling schemes by means of numerical examples. Comparisons show that the sampling design based on Ali-Silvey distance measures result in superior performance.