基于小波变换的带宽边缘自动盲检测方法

R. Hatoum, A. Ghaith, G. Pujolle
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引用次数: 3

摘要

边缘检测在许多应用领域都是一项重要的任务。信号的不连续结构可以反映信号的某些特征。一般来说,数学信号变换比原始信号具有更多的特征。因此,为了在完全盲的环境中分析截获的信号,人们可以从信号频谱通过傅里叶变换提供的信息中获益。在检测到光谱后,必须应用特征提取方法。本文采用了小波变换,因为它具有很好的分析信号的能力。本文还介绍了一种在确定频率范围内自动识别带宽信号边界的改进算法。该算法基于小波变换模的局部最大值。在盲条件和噪声环境下,该方法具有良好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An automatic approach to blindly detect bandwidth edges based on the wavelet transform
Edges Detection is a significant task in many fields of application. Some signal features can be reflected by their discontinuous structure. In general, a mathematical signal transform carries more features than a raw signal. Thus, for analyzing an intercepted signal in a totally blind environment, one can benefit from the information the signal spectrum offers through the Fourier Transform. After sensing the spectrum, the characteristics extraction method must be applied. In this paper, the Wavelet Transform is used, as it exhibits excellent ability to analyze a signal. Also introduced in this paper is an improved algorithm that automatically identifies bandwidth signal boundaries in a determined frequency range. The proposed algorithm is based on the local maxima of the Wavelet Transform modulus. In blind conditions and in a noisy environment, this approach grants good performance.
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