Testing stationarity with time-frequency surrogates
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[1] James Theiler,et al. Testing for nonlinearity in time series: the method of surrogate data , 1992 .
[2] Nello Cristianini,et al. An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .
[3] Simon J. Godsill,et al. Detection of abrupt spectral changes using support vector machines an application to audio signal segmentation , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[4] John B. Shoven,et al. I , Edinburgh Medical and Surgical Journal.
[5] W. Martin. Measuring the degree of non-stationarity by using the Wigner-Ville spectrum , 1984, ICASSP.
[6] Jun Xiao,et al. Multitaper time-frequency reassignment , 2006, 2006 14th European Signal Processing Conference.
[7] Jun Xiao,et al. Testing Stationarity with Surrogates - A One-Class SVM Approach , 2007, 2007 IEEE/SP 14th Workshop on Statistical Signal Processing.
[8] Georgios B. Giannakis,et al. Bibliography on cyclostationarity , 2005, Signal Process..
[9] M. Basseville. Distance measures for signal processing and pattern recognition , 1989 .
[10] Jun Xiao,et al. Multitaper Time-Frequency Reassignment for Nonstationary Spectrum Estimation and Chirp Enhancement , 2007, IEEE Transactions on Signal Processing.
[11] C. Doncarli,et al. Stationarity index for abrupt changes detection in the time-frequency plane , 1996, IEEE Signal Processing Letters.
[12] Bernhard Schölkopf,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2005, IEEE Transactions on Neural Networks.
[13] Richard G. Baraniuk,et al. Multiple Window Time Varying Spectrum Estimation , 2000 .
[14] Richard A. Silverman,et al. Locally stationary random processes , 2018, IRE Trans. Inf. Theory.
[15] C. Keylock,et al. Constrained surrogate time series with preservation of the mean and variance structure. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.
[16] Patrick Flandrin,et al. Time-Frequency/Time-Scale Analysis , 1998 .
[17] Paul Honeine,et al. Time-Frequency Learning Machines , 2007, IEEE Transactions on Signal Processing.
[18] P. Flandrin,et al. Detection of changes of signal structure by using the Wigner-Ville spectrum , 1985 .
[19] Anthony Widjaja,et al. Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond , 2003, IEEE Transactions on Neural Networks.
[20] Schreiber,et al. Improved Surrogate Data for Nonlinearity Tests. , 1996, Physical review letters.
[21] S. Mallat,et al. Adaptive covariance estimation of locally stationary processes , 1998 .