| 1. | Analysis of sleep staging by time - window complexity sequence of eeg
基于时窗复杂度序列的睡眠脑电分析 |
| 2. | Auto correlating window
自相关时窗 |
| 3. | Extracting p - wave and s - wave information for full - wave logging by using long - short time window energy ratio method
长短时窗能量比法提取声波全波列测井纵横波信息 |
| 4. | The extraordinary plasticity of the young brain occurs only during a narrow window of time known as the critical period
未成熟大脑的这一奇特可塑性仅见于被称为临界期的一段短暂的时间（时窗）内。 |
| 5. | Component even comes with a pre - registered listener , so the pane will scroll when it has focus and the user moves the wheel
组件甚至随预注册的侦听器一起提供，所以当这个组件获得焦点且用户移动鼠标滚轮时窗格将会滚动。 |
| 6. | The instant spectrum analysis technology of this kind can get precise results of time and frequency analysis , and avoid the problem of time window
以小波变换为基础的瞬时谱分析技术能得到精确的时频分析结果，同时避免了时窗问题。 |
| 7. | Since it is hard to choose time window in practice and analyze the error quantitatively , there are usually deviations in the evaluation of amplitude spectrum
由于在实际运用中，以傅里叶变换相关的算法的时窗问题，难以选择好时窗长度，而且无法定量分析时窗长度产生的偏差，因而会使振幅谱的估算产生偏差。 |
| 8. | The algorithm used in the past was usually based on fourier transform , but there are clearly limitations in the method , because the seismic amplitude spectrum that it evaluated is the function of time windows
如果所选时窗过短，振幅谱会与变换窗函数褶积，失去频率的局部化特徵，而且过短的时窗会使子波的旁瓣呈现为单一反射的假像。 |
| 9. | Based on the existing spectral independent component analysis ( spectral ica ) and non - negative constrained decomposition , a moving time window is introduced , and multiple dominant spectral components are extracted within the short - time window
结合已有的频域独立成分分析方法以及带约束的非负分解处理，引入时间滑动窗口，在短时窗内动态提取多重主导功率频谱。 |
