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用于处理正交信号的定向双树复小波包变换

Directional dual-tree complex wavelet packet transforms for processing quadrature signals.

作者信息

Serbes Gorkem, Gulcur Halil Ozcan, Aydin Nizamettin

机构信息

Biomedical Engineering Department, Bahcesehir University, Besiktas, Istanbul, Turkey.

Biomedical Engineering Institute, Bogazici University, Kandilli, Istanbul, Turkey.

出版信息

Med Biol Eng Comput. 2016 Mar;54(2-3):295-313. doi: 10.1007/s11517-014-1224-0. Epub 2014 Nov 12.

DOI:10.1007/s11517-014-1224-0
PMID:25388779
Abstract

Quadrature signals containing in-phase and quadrature-phase components are used in many signal processing applications in every field of science and engineering. Specifically, Doppler ultrasound systems used to evaluate cardiovascular disorders noninvasively also result in quadrature format signals. In order to obtain directional blood flow information, the quadrature outputs have to be preprocessed using methods such as asymmetrical and symmetrical phasing filter techniques. These resultant directional signals can be employed in order to detect asymptomatic embolic signals caused by small emboli, which are indicators of a possible future stroke, in the cerebral circulation. Various transform-based methods such as Fourier and wavelet were frequently used in processing embolic signals. However, most of the times, the Fourier and discrete wavelet transforms are not appropriate for the analysis of embolic signals due to their non-stationary time-frequency behavior. Alternatively, discrete wavelet packet transform can perform an adaptive decomposition of the time-frequency axis. In this study, directional discrete wavelet packet transforms, which have the ability to map directional information while processing quadrature signals and have less computational complexity than the existing wavelet packet-based methods, are introduced. The performances of proposed methods are examined in detail by using single-frequency, synthetic narrow-band, and embolic quadrature signals.

摘要

包含同相和正交相位分量的正交信号在科学和工程的各个领域的许多信号处理应用中都有使用。具体而言,用于无创评估心血管疾病的多普勒超声系统也会产生正交格式的信号。为了获得血流方向信息,必须使用非对称和对称相位滤波技术等方法对正交输出进行预处理。这些所得的方向信号可用于检测由小栓子引起的无症状栓塞信号,这些栓子是脑循环中未来可能发生中风的指标。各种基于变换的方法,如傅里叶变换和小波变换,经常用于处理栓塞信号。然而,大多数情况下,由于其非平稳时频特性,傅里叶变换和离散小波变换不适用于栓塞信号的分析。另外,离散小波包变换可以对时频轴进行自适应分解。在本研究中,引入了方向离散小波包变换,它能够在处理正交信号时映射方向信息,并且计算复杂度比现有的基于小波包的方法更低。通过使用单频、合成窄带和栓塞正交信号详细研究了所提出方法的性能。

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本文引用的文献

1
Denoising performance of modified dual-tree complex wavelet transform for processing quadrature embolic Doppler signals.改进的双树复小波变换在处理正交栓塞多普勒信号中的去噪性能。
Med Biol Eng Comput. 2014 Jan;52(1):29-43. doi: 10.1007/s11517-013-1114-x. Epub 2013 Sep 19.
2
STFT or CWT for the detection of Doppler ultrasound embolic signals.STFT 或 CWT 在检测多普勒超声栓塞信号中的应用。
Int J Numer Method Biomed Eng. 2013 Sep;29(9):964-76. doi: 10.1002/cnm.2546. Epub 2013 Apr 10.
3
Symmetrical modified dual tree complex wavelet transform for processing quadrature Doppler ultrasound signals.
用于处理正交多普勒超声信号的对称改进双树复数小波变换。
Annu Int Conf IEEE Eng Med Biol Soc. 2011;2011:4816-9. doi: 10.1109/IEMBS.2011.6091193.
4
Driver drowsiness classification using fuzzy wavelet-packet-based feature-extraction algorithm.基于模糊小波包的特征提取算法的驾驶员瞌睡分类。
IEEE Trans Biomed Eng. 2011 Jan;58(1):121-31. doi: 10.1109/TBME.2010.2077291. Epub 2010 Sep 20.
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A novel criterion of wavelet packet best basis selection for signal classification with application to brain-computer interfaces.一种用于基于信号分类的小波包最佳基选择的新准则及其在脑机接口中的应用。
IEEE Trans Biomed Eng. 2009 Nov;56(11 Pt 2):2734-8. doi: 10.1109/TBME.2009.2028014. Epub 2009 Jul 31.
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Best wavelet packet bases in a rate-distortion sense.最佳率失真意义下的小波包基。
IEEE Trans Image Process. 1993;2(2):160-75. doi: 10.1109/83.217221.
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Compression of biomedical signals with mother wavelet optimization and best-basis wavelet packet selection.基于母小波优化和最优基小波包选择的生物医学信号压缩
IEEE Trans Biomed Eng. 2007 Dec;54(12):2186-92. doi: 10.1109/tbme.2007.896596.
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Embolic Doppler ultrasound signal detection using discrete wavelet transform.使用离散小波变换的栓塞性多普勒超声信号检测
IEEE Trans Inf Technol Biomed. 2004 Jun;8(2):182-90. doi: 10.1109/titb.2004.828882.
9
Online automated detection of cerebral embolic signals using a wavelet-based system.使用基于小波的系统对脑栓塞信号进行在线自动检测。
Ultrasound Med Biol. 2004 May;30(5):647-53. doi: 10.1016/j.ultrasmedbio.2004.03.009.
10
The use of the wavelet transform to describe embolic signals.使用小波变换来描述栓塞信号。
Ultrasound Med Biol. 1999 Jul;25(6):953-8. doi: 10.1016/s0301-5629(99)00052-6.