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本文提出了一种信号检测系统,用来检测在非高斯噪声中的微弱信号。它是一种无记忆非线性(ZMNL)检测器,对于一个离散序列进行ZMNL运算后与一门限值相比较,即能判决有无信号存在。检测器是根据Neyman—Pearson准则设计的结构,它仅对微弱信号是最佳的,因而称为局部最佳检测系统。 如何衡量这种系统性能的好坏,用的是渐近相对效率这一概念。本文讨论了在某些非高斯噪声情况下渐近相对效率的计算。
This paper presents a signal detection system to detect weak signals in non-Gaussian noise. It is a memoryless nonlinearity (ZMNL) detector that performs a ZMNL operation on a discrete sequence to compare with a threshold to determine whether a signal exists or not. The detector is a structure designed according to the Neyman-Pearson criterion, which is only optimal for weak signals and is therefore called the local best detection system. How to measure the performance of this system is good or bad, using the concept of asymptotic relative efficiency. This article discusses the calculation of asymptotic relative efficiency with some non-Gaussian noise.