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。
The relationships between traffic parameters, such as the ramp flow, speed, density and mainline flow at the ramp junction, are established by mapping time-space plane to speed-density plane.
积分后，得到了匝道单车道流量与匝道连接处速度、密度和流量的理论关系模型。
The relationships between traffic parameters, such as the ramp flow, speed, density and mainline flow at the ramp junction, are established by mapping time-space plane to speed-density plane.
积分后，得到了匝道单车道流量与匝道连接处速度、密度和流量的理论关系模型。
应用推荐