Issue Date: 6-7 March 2010rnrntOn page(s): rnt115rnttrn- 118rnrnrnLocation: Wuhan, ChinarnrnPrint ISBN: 978-1-4244-6388-6rnrnrnrnttrnDigital Object Identifier: href='http://dx.doi.org/10.1109/ETCS.2010.600' target='_blank'>10.1109/ETCS.2010.600 rnrnDate of Current Version: trnrnt2010-05-06 14:33:50.0rnrnt rntt class="body-text">rntname="Abstract">>Abstractrn>Blind source separation (BSS) allows the recovery of unknown signals from observed signals mixed by an unknown propagation medium, and is a promising technique for signal processing and data analysis. In ultrasonic nondestructive evaluation (NDE), BSS can serve at least three purposes: defect classification, system modeling and noise reduction. This paper discusses the appl;
Blind source separation (BSS); independent component analysis (ICA); nondestructive evaluation (NDE); signal processing;
机译:使用盲源分离的超声NDE信号的噪声消除
机译:利用盲源分离消除超声NDE信号的噪声
机译:基于二维H∞的盲去卷积用于图像增强及其在超声NDE中的应用
机译:盲源分离在超声无损检测中的应用
机译:盲源分离,用于超声成像中的选择性组织运动测量。
机译:盲源分离–基于亚微米的运动检测器超声成像中的周期性位移
机译:盲源分离的递归方法及其在声信号实时分离中的应用