Linearization effectively improves time resolution of the received images, which makes the characteristics of the defect more markedly and leads to more accurate quantitative measurement.
线性化处理技术有效地提高了图像的时间分辨力，使面状缺陷的信号和图像的特征更明显，进而使定位定量更为精确。
The good localization characteristics of wavelet functions in both time and frequency space allowed hierarchical multi-resolution learning of input-output data mapping.
利用小波变换所具有的良好的时频分析特性，实现了输入输出之间映射关系的多分辨学习。
The good localization characteristics of wavelet functions in both time and frequency space allow hierarchical multi-resolution learning of input-output data mapping.
由于小波变换在时间和频率空间具有良好的定位特性，使小波神经网络可对输入、输出数据进行多分辨的学习训练。
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