Analysis of the Doppler signals using largest Lyapunov exponent and correlation dimension in healthy and stenosed internal carotid artery patients
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[1] Fraser,et al. Independent coordinates for strange attractors from mutual information. , 1986, Physical review. A, General physics.
[2] Mingzhou Ding,et al. Estimating correlation dimension from a chaotic time series: when does plateau onset occur? , 1993 .
[3] Theiler,et al. Spurious dimension from correlation algorithms applied to limited time-series data. , 1986, Physical review. A, General physics.
[4] Sadik Kara,et al. Recognition of early phase of atherosclerosis using principles component analysis and artificial neural networks from carotid artery Doppler signals , 2006, Expert Syst. Appl..
[5] Theiler. Statistical precision of dimension estimators. , 1990, Physical review. A, Atomic, molecular, and optical physics.
[6] H. Kantz,et al. Nonlinear time series analysis , 1997 .
[7] Inan Güler,et al. Detecting variability of internal carotid arterial Doppler signals by Lyapunov exponents. , 2004, Medical engineering & physics.
[8] Akihiko Kikuchi,et al. Nonlinear analyses of heart rate variability in normal and growth-restricted fetuses. , 2006, Early human development.
[9] Fatma Latifoglu,et al. Diagnosis of atherosclerosis from carotid artery Doppler signals as a real-world medical application of artificial immune systems , 2007, Expert Syst. Appl..
[10] B. Sigel,et al. A brief history of Doppler ultrasound in the diagnosis of peripheral vascular disease. , 1998, Ultrasound in medicine & biology.
[11] Anastasios Bezerianos,et al. Nonlinear analysis of the performance and reliability of wavelet singularity detection based denoising for doppler ultrasound fetal heart rate signals , 1999, Int. J. Medical Informatics.
[12] Simon Haykin,et al. Detection of signals in chaos , 1995, Proc. IEEE.
[13] D. T. Kaplan,et al. Aging and the complexity of cardiovascular dynamics. , 1991, Biophysical journal.
[14] J. Fell,et al. Resonance-like phenomena in Lyapunov calculations from data reconstructed by the time-delay method , 1994 .
[15] F. Takens. Detecting strange attractors in turbulence , 1981 .
[16] P B Persson,et al. Chaos in the cardiovascular system: an update. , 1998, Cardiovascular research.
[17] Leonard A. Smith. Intrinsic limits on dimension calculations , 1988 .
[18] I. Johnstone,et al. Ideal spatial adaptation by wavelet shrinkage , 1994 .
[19] Metin Akay,et al. Nonlinear Biomedical Signal Processing Vol. II: Dynamic Analysis and Modeling , 2000 .
[20] L. Tsimring,et al. The analysis of observed chaotic data in physical systems , 1993 .
[21] A. Wolf,et al. Determining Lyapunov exponents from a time series , 1985 .
[22] James Theiler,et al. Estimating fractal dimension , 1990 .
[23] Tsutomu Takahashi,et al. Carotid turbulent flow observed by convergent color Doppler flowmetry in silent cerebral infarction , 2002, The International Journal of Cardiovascular Imaging.
[24] D. Evans. Doppler Ultrasound: Physics Instrumentation and Clinical Applications , 1989 .
[25] P. Grassberger,et al. Measuring the Strangeness of Strange Attractors , 1983 .
[26] O. Joakimsen,et al. Prediction of mortality by ultrasound screening of a general population for carotid stenosis: the Tromsø Study. , 2000, Stroke.
[27] Marc Revol,et al. Detection of Hemodynamic Turbulence in Experimental Stenosis: An in vivo Study in the Rat Carotid Artery , 2002, Journal of Vascular Research.
[28] C. Stam,et al. Nonlinear transcranial Doppler analysis demonstrates age-related changes of cerebral hemodynamics. , 1996, Ultrasound in medicine & biology.
[29] Side He,et al. A comparison of the wavelet and short-time fourier transforms for Doppler spectral analysis. , 2003, Medical engineering & physics.
[30] Peter R. Hoskins,et al. Haemodynamics and blood flow , 2006 .
[31] Yüksel Özbay,et al. Effects of window types on classification of carotid artery Doppler signals in the early phase of atherosclerosis using complex-valued artificial neural network , 2007, Comput. Biol. Medicine.
[32] Yu Zhang,et al. Doppler ultrasound signal denoising based on wavelet frames. , 2001, IEEE transactions on ultrasonics, ferroelectrics, and frequency control.
[33] D. Ruelle,et al. Fundamental limitations for estimating dimensions and Lyapunov exponents in dynamical systems , 1992 .
[34] F. Takens,et al. On the nature of turbulence , 1971 .
[35] Ong Wai Sing,et al. Heart rate analysis in normal subjects of various age groups , 2004, Biomedical engineering online.
[36] A. Pries,et al. Deterministic nonlinear characteristics of in vivo blood flow velocity and arteriolar diameter fluctuations , 2004, Physics in medicine and biology.
[37] Aneta Stefanovska,et al. Reconstructing cardiovascular dynamics , 1997 .
[38] Ingrid Daubechies,et al. Ten Lectures on Wavelets , 1992 .
[39] L. Cao. Practical method for determining the minimum embedding dimension of a scalar time series , 1997 .
[40] David L. Donoho,et al. De-noising by soft-thresholding , 1995, IEEE Trans. Inf. Theory.
[41] L Glass,et al. Time series analysis of complex dynamics in physiology and medicine. , 1993, Medical progress through technology.
[42] D. Ruelle,et al. Ergodic theory of chaos and strange attractors , 1985 .
[43] Elif Derya Übeyli,et al. Spectral analysis of internal carotid arterial Doppler signals using FFT, AR, MA, and ARMA methods , 2004, Comput. Biol. Medicine.
[44] D. Ku. BLOOD FLOW IN ARTERIES , 1997 .