Short works

Books : reviews

Edward Ott, Tim D. Sauer, James A. Yorke, eds.
Coping with Chaos: analysis of chaotic data and the exploitation of chaotic systems.
Wiley. 1994

The first unified presentation of new developments in the analysis and exploitation of chaotic systems…

Mathematicians have been aware of chaotic dynamics since Poincaré’s work at the turn of the century. But, as the turn of yet another century approaches, physical scientists and engineers have begun to use their understanding of chaos theory to analyze chaotic experimental time series data. Some researchers have even used the presence of chaos to achieve practical goals. To do this, they have had to work with dynamical processes for which the equations were either not known or were too complex to be useful. In other words, they have been coping with chaos.

Coping With Chaos is the first book to bring together recent advances in the interpretive and practical applications of chaos, which hold great promise for broad applicability throughout the physical sciences and engineering. Together with an introduction to chaos theory, this book provides detailed reports on methods of analyzing experimental time series data from chaotic systems and studies in which the unique attributes of chaos are put to practical use. Topics discussed in this book include:

• Theory of chaotic dynamics
• Embedding techniques for the analysis of experimental data
• Calculation of dimension and Lyapunov exponents
• Determination of periodic orbits and symbolic dynamics
• Prediction of chaotic time series
• Noise filtering of chaotic data
• Control of chaotic systems
• The use of Chaotic signals for communication
• And more


George Sugihara, Robert M. May. Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series. Nature, 344, 734-741. 1990
Norman H. Packard, James P. Crutchfield, J. Doyne Farmer, Robert S. Shaw. Geometry from a time series. Phys. Rev. Lett. 45:712. 1980
D. S. Broomhead, Gregory P. King. Extracting qualitative dynamics from experimental data. Physica D 20:217-236. 1986
Matthew B. Kennel, Reggie Brown, Henry D. I. Abarbanel. Determining embedding dimension for phase-space reconstruction using a geometrical construction. Phys. Rev. A 45:3403-3411. 1992
Daniel T. Kaplan, Leon Glass. Direct test for determinism in a time series. Phys. Rev. Lett. 68:427-430. 1992
A. M. Albano, J. Muench, C. Schwartz, Alistair I. Mees, P. E. Rapp. Singular-value decomposition and the Grassberger-Procaccia algorithm. Phys. Rev. A 38:3017. 1988
Jean-Pierre Eckmann, David Ruelle. Fundamental limitations for estimating dimensions and Lyapunov exponents in dynamical systems. Physica D 56:185. 1992
Mingzhou Ding, Celso Grebogi, Edward Ott, Tim D. Sauer, James A. Yorke. Plateau onset for correlation dimension: When does it occur?. Phys. Rev. Lett. 70:3872. 1993
James Theiler, Stephen G. Eubank, Andre Longtin, Bryan Galdrikian, J. Doyne Farmer. Testing for nonlinearity in time series: The method of surrogate data. Physica D 58:77. 1992
A. Brandstater, Harry L. Swinney. Strange attractors in weakly turbulent Couette-Taylor flow. Phys. Rev. A 35:2207. 1987
John Guckenheimer, George Buzyna. Dimension measurements for geostrophic turbulence. Phys. Rev. Lett. 51:1438. 1983
Jean-Pierre Eckmann, S. Oliffson Kamphorst, David Ruelle, S. Ciliberto. Liapunov exponents from time series. Phys. Rev. A 34:4971. 1986
Paul Bryant, Reggie Brown, Henry D. I. Abarbanel. Lyapunov exponents from observed time series. Phys. Rev. Lett. 65:1523. 1990
Ulrich Parlitz. Identification of true and spurious Lyapunov exponents from time series. Int. J. Bif. Chaos 2:155. 1992
Daniel P. Lathrop, Eric J. Kostelich. Characterization of an experimental strange attractor by periodic orbits. Phys. Rev. A 40:4028. 1989
L. Flepp, R. Holzner, E. Brun, M. Finardi, Remo Badii. Model identification by periodic-orbit analysis for NMR-laser chaos. Phys. Rev. Lett. 67:2244. 1991
John C. Sommerer, William L. Ditto, Celso Grebogi, Edward Ott, Mark L. Spano. Experimental confirmation of the theory for critical exponents of crises. Phys. Lett. A 153:105. 1991
F. Papoff, A. Fioretti, E. Arimondo, G.B. Mindlin, H. Solari, Robert Gilmore. Structure of chaos in the laser with saturable absorber. Phys. Rev. Lett. 68:1128. 1992
J. Doyne Farmer, John J. Sidorowich. Predicting chaotic time series. Phys. Rev. Lett. 59:845. 1987
Martin Casdagli. Nonlinear prediction of chaotic time series. Physica D 35:335. 1989
Tim D. Sauer. Time series prediction using delay coordinate embedding. 1993
Eric J. Kostelich, James A. Yorke. Noise reduction in dynamical systems. Phys. Rev. A 38:1649. 1988
Peter Grassberger, Rainer Hegger, Holger Kantz, Carsten Schaffrath, Thomas Schreiber. On noise reduction methods for chaotic data. Chaos 3:127. 1993
Stephen M. Hammel. A noise reduction method for chaotic systems. Phys. Lett. A 148:421. 1990
Edward Ott, Celso Grebogi, James A. Yorke. Controlling chaos. Phys. Rev. Lett. 64:1196. 1990
Ute Dressler, Gregor Nitsche. Controlling chaos using time delay coordinates. Phys. Rev. Lett. 68:1. 1992
Filipe J. Romeiras, Celso Grebogi, Edward Ott, W. P. Dayawansa. Controlling chaotic dynamical systems. Physica D 58:165. 1992
Hua Wang, Eyad H. Abed. Bifurcation control of chaotic dynamical systems. Proc. IFAC Nonlinear Control Systems Design Symp.. 1992
William L. Ditto, S. N. Rauseo, Mark L. Spano. Experimental control of chaos. Phys. Rev. Lett. 65:3211. 1990
Jonathan Singer, Y.-Z. Wang, Haim H. Bau. Controlling a chaotic system. Phys. Rev. Lett. 66:1123. 1991
Alan Garfinkel, Mark L. Spano, William L. Ditto, James N. Weiss. Controlling cardiac chaos. Science 257:1230. 1992
E. R. Hunt. Stabilizing high-period orbits in a chaotic system: The diode resonator. Phys. Rev. Lett. 67:1953. 1991
Zelda Gills, Christina Iwata, Rajarshi Roy, Ira B. Schwartz, Ioana Triandaf. Tracking unstable steady states: Extending the stability regime of a multimode laser system. Phys. Rev. Lett. 69:3169. 1992
Valery Petrov, Vilmos Gaspar, Jonathan Masere, Kenneth Showalter. Controlling chaos in the Belousov-Zhabotinsky reaction. Nature 361:240. 1993
Troy Shinbrot, William L. Ditto, Celso Grebogi, Edward Ott, Mark L. Spano, James A. Yorke. Using the sensitive dependence of chaos (the "butterfly effect") to direct trajectories in an experimental chaotic system. Phys. Rev. Lett. 68:2863. 1992
Alfred Hubler, E. Luscher. Resonant stimulation and control of nonlinear oscillators. Naturwissenschaften 76: 67. 1989
E. Atlee Jackson. The entrainment and migration controls of multiple-attractor systems. Phys. Lett. A 151:478. 1990
Louis M. Pecora, Thomas L. Carroll. Synchronization in chaotic systems. Phys. Rev. Lett. 64:821. 1990
Kevin M. Cuomo, Alan V. Oppenheim. Circuit implementation of synchronized chaos with applications to communication. Phys. Rev. Lett. 71:65. 1993
Scott Hayes, Celso Grebogi, Edward Ott. Communicating with chaos. Phys. Rev. Lett. 70:3031. 1993
Paul So, Edward Ott, W. P. Dayawansa. Observing chaos: Deducing and tracking the state of a chaotic system from limited observation. Phys. Lett. A 176:421. 1993

Kathleen T. Alligood, Tim D. Sauer, James A. Yorke.
Chaos : an introduction to dynamical systems.
Springer. 1996

Chaos: An Introduction To Dynamical Systems was developed and class-tested by a distinguished team of authors at two universities through their teaching of courses based on the material. Intended for courses in nonlinear dynamics offered in either mathematics or physics, the text requires only calculus, differential equations, and linear algebra as prerequisites.

Spanning the wide reach of nonlinear dynamics throughout mathematics and natural and physical science, Chaos: An Introduction To Dynamical Systems develops and explains the most intriguing and fundamental elements of the topic, and examines their broad implications.

Among the major topics included are discrete dynamical systems, chaos, fractals, nonlinear differential equations, and bifurcations. The text also features Lab Visits, short reports that illustrate relevant concepts from the physical, chemical, and biological sciences, drawn from the scientific literature. There are Computer Experiments throughout the text that present opportunities to explore dynamics through computer simulation, designed to be used with any standard software package. And each chapter ends with a Challenge, which provides students with a tour through an advanced topic in the form of an extended exercise.