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Selection of optimal wavelet basis for singularity detection of non-stationary signal

机译:非平稳信号奇异性检测的最优小波基选择

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By using wavelet transform modulus maximum principle for non-stationary signal singularity detection is a kind of very good method. Through to the various wavelet singularity extracted, the analysis results can be divided into four types: accurate location, the approximate location, overlapping effect, rim effect. According to the classification we learn the optimal wavelet basis should has the following features: the optimum wavelet basis should have strong ability of detecting and precision, and at the same time the influence of overlap and rim should be as small as possible. According to these characteristics, a discriminant function is constructed. The wavelet basis makes the largest discriminant function value is optimal. The experimental results show that the method in this paper according to find out the optimum wavelet basis did more than other wavelet detection effect better.
机译:利用小波变换模极大值原理进行非平稳信号奇异性检测是一种非常好的方法。通过对各种小波奇异点的提取,分析结果可以分为四种类型:精确位置,近似位置,重叠效应,边缘效应。根据分类,我们学习最优小波基应该具有以下特征:最优小波基应具有较强的检测能力和精度,同时重叠和边缘的影响应尽可能小。根据这些特征,构造了判别函数。小波基使得最大的判别函数值是最优的。实验结果表明,该方法在寻找最优小波基的基础上比其他小波检测效果更好。

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