Biomedical Engineering Reference
In-Depth Information
[57]
Bloomfield, P., Fourier Analysis of Time Series: An Introduction, New York: Wiley, 1976.
[58]
Oppenheim, A. V., et al., “Signal Processing in the Context of Chaotic Signals,” IEEE
International Conference on Acoustics, Speech, and Signal Processing, Vol. 4, 1992,
pp. 117-120.
[59]
Nikias, C. L., and A. Petropulu, Higher-Order Spectra Analysis, Englewood Cliffs, NJ:
Prentice-Hall, 1993.
[60]
Nikias, C. L., and J. Mendel, “Signal Processing with Higher-Order Spectra,” IEEE Signal
Processing Magazine, 1993, pp. 10-37.
[61]
Abarbanel, H. D. I., Analysis of Observed Chaotic Data , New York: Springer-Verlag,
1996.
[62]
Holden, A. V., Chaos-Nonlinear Science: Theory and Applications , Manchester, U.K.:
Manchester University Press, 1986.
[63]
Wolf, A., et al., “Determining Lyapunov Exponents from a Time Series,” Physica D,
Vol. 16, 1985, pp. 285-317.
[64]
Grassberger, P., “Generalized Dimension of Strange Attractors,” Phys. Lett., Vol. 97A,
No. 6, 1983, pp. 227-230.
[65]
Prichard, D., and J. Theiler, “Generalized Redundancies for Time Series Analysis,” Physica
D, Vol. 84, 1995, pp. 476-493.
[66]
Takens, F., “Detecting Strange Attractors in Turbulence in Dynamic Systems and Turbu-
lence,” in Lecture Notes in Mathematics, D. A. Rand and L. S. Young, (eds.), New York:
Springer-Verlag, 1980, pp. 366-376.
[67]
Mayer-Kress, G., Dimensions and Entropies in Chaotic Systems , New York: Springer,
1986.
[68]
Packard, N. H., et al., “Geometry from Time Series,” Phys. Rev. Lett., Vol. 45, 1980,
pp. 712-716.
[69]
Fraser, A. M., and H. L. Swinney, “Independent Coordinates for Strange Attractors from
Mutual Information,” Phys. Rev. A, Vol. 33, 1986, pp. 1134-1138.
[70]
Iasemidis, L. D., J. C. Sackellares, and R. S. Savit, “Quantification of Hidden Time Depend-
encies in the EEG Within the Framework of Nonlinear Dynamics,” in Nonlinear Dynamic
Analysis of the EEG, B. H. Jansen and M. E. Brandt, (eds.), Singapore: World Scientific,
1993, pp. 30-47.
[71]
Sackellares, J. C., et al., “Epilepsy—When Chaos Fails,” in Chaos in Brain?, K. Lehnertz et
al., (eds.), Singapore: World Scientific, 2000, pp. 112-133.
[72]
Theiler, J., “Spurious Dimension from Correlation Algorithm Applied to Limited Time
Series Data,” Phys. Rev. A, Vol. 34, No. 3, 1986, pp. 2427-2432.
[73]
Kantz, H., and T. Schreiber, Nonlinear Time Series Analysis, Cambridge, MA: Cambridge
University Press, 1997.
[74]
Albano, A. M., et al., “Singular Value Decomposition and Grassberger-Procaccia Algo-
rithm,” Phys. Rev. A, Vol. 38, No. 6, 1988, pp. 3017-3026.
[75]
Lopes da Silva, F., “EEG Analysis: Theory and Practice; Computer-Assisted EEG Diagno-
sis: Pattern Recognition Techniques,” in Electroencephalography: Basic Principles, Clinical
Applications, and Related Fields, 5th ed., E. Niedermeyer and F. Lopes da Silva, (eds.), Bal-
timore, MD: Lippincott Williams & Wilkins, 2004, pp. 871-919.
[76]
Iasemidis, L. D., et al., “Spatiotemporal Transition to Epileptic Seizures: A Nonlinear
Dynamic Analysis of Scalp and Intracranial EEG Recordings,” in Spatiotemporal Models in
Biological and Artificial Systems, F. L. Silva, J. C. Principe, and L. B. Almeida, (eds.),
Amsterdam: IOS Press, 1997, pp. 81-88.
[77]
Babloyantz, A., and A. Destexhe, “Low Dimensional Chaos in an Instance of Epilepsy,”
Proc. Natl. Acad. Sci. USA, Vol. 83, 1986, pp. 3513-3517.
[78]
Kostelich, E. J., “Problems in Estimating Dynamics from Data,” Physica D, Vol. 58, 1992,
pp. 138-152.
Search WWH ::




Custom Search