本文研究了非高斯噪声中信号的检测，采用多层感知器神经网络作为检测器。
In this paper, the authors study the detection of signals in non-Gaussian noise, and employ a multilayer perceptron neural network as a detector.
在非平稳非高斯背景噪声下，使用经典信号检测理论对信号进行检测往往难以达到理想的效果。
If the background noise is nonstationary and non-Gaussian, the effect of classic signal detection theory is not satisfying.
本文将小波包变换用于非高斯噪声统计特性的研究，提出一种新的非高斯分布噪声下的信号检测算法。
In the dissertation, it puts wavelet-packet decomposition into the study on non-gaussian noise. It offers a new signal dection method under non-gaussian noise backgroud.
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