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。
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。
Objective To examine the spatial distribution and dispersion of repolarization using space-time map of body surface potential mapping (BSPM) and their clinical value.
目的用体表心电标测时空图法探讨复极离散空间分布和临床价值。
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