Description: pam我们考虑常见的插值(抽取)运算和滤波器级联的情形，在实际的插值(余
:)运算中，为了避免信号在经过插值(抽取)后出现混盛现象，保证能无失多
恢复信号，我们常常在插值运算之后(抽取运算之前)加上插值(抽取)滤公
时信号进行带限，如图2.10左边所示。
-we consider common interpolation (extraction) and Operational FILTER circumstances, In the actual interpolation (I :) operator, in order to avoid signal after interpolation (taken) after mixed Sheng, guarantee that it will lose no more than restore signals We often after the interpolation operation (from operations before), plus interpolation (extraction) filter when public signal band-limited, 2.10 figure shown in the left side. Platform: |
Size: 1205248 |
Author:陈重 |
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Description: 从混有呼吸噪音的信号中，提取呼吸信号，完成去除呼吸信号的功能-Mixed with noise from the respiratory signal, respiratory signal extraction, complete removal of the function of respiratory signal Platform: |
Size: 2048 |
Author:张婷婷 |
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Description: 针对滚动轴承复合故障信号特征难以分离的问题， 提出将双树复小波变换和独立分量分析( ICA) 结合的故障诊断方
法 该方法首先将非平稳的故障信号通过双树复小波变换分解为若干不同频带的分量 由于各个分量存在一定的频率混叠， 对
故障信号特征提取有很大的干扰， 进而引入 ICA 对各个分量所组成的混合信号进行盲源分离， 从而尽可能消除频率混叠 最后
对从混合信号中分离出来的独立分量信号进行希尔伯特包络解调， 即可实现对复合故障特征信息的分离和故障识别-Aiming at the difficulty of separating the fault feature from compound rolling bearing fault signal，a new
fault diagnosis method is proposed based on dual-tree complex wavelet transform ( DT-CWT) and independent com-
ponent analysis ( ICA) ． Firstly，DT-CWT is used to decompose the non-stationary fault vibration signal into several
components with different frequency bands． Because frequency aliasing exists in the components，this problem dis-
turbs the feature extraction of the fault signal． Then，ICA is introduced to perform blind source separation on the
mixed signal consisting of various components to eliminate the frequency aliasing as far as possible． Finally，Hilbert
envelope decomposition is performed on the independent signal components separated from the mixed signal． Thus
the compound fault feature information can be separated，and the fault identification is achieved． Platform: |
Size: 927744 |
Author:侯蒙蒙 |
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Search - extraction of signal from mixed signal