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Nonlinear Dynamics

, Volume 41, Issue 1–3, pp 47–67 | Cite as

Dimensionality Reduction Using Secant-Based Projection Methods: The Induced Dynamics in Projected Systems

  • D. S. Broomhead
  • M. J. Kirby
Article

Abstract

In previous papers we have developed an approach to the data reduction problem which is based on a well-known, constructive proof of Whitney’s embedding theorem [Broomhead, D. S. and Kirby, M., SIAM Journal of Applied Mathematics 60(6), 2000, 2114–2142; Broomhead, D. S. and Kirby, M., Neural Computation 13, 2001, 2595–2616]. This approach involves picking projections of the high-dimensional system which are optimised in the sense that they are easy to invert. This is done by considering the effect of the projections on the set of unit secants constructed from the data. In the present paper we discuss the implications of this idea in the case that the high-dimensional data is generated by a dynamical system. We ask if the existence of an easily invertible projection leads to practical methods for the construction of an equivalent, low-dimensional dynamical system. The paper consists of a review of the secant-based projection method and simple methods for finding good representations of the (nonlinear) inverse of the projections. We then discuss two variants of a way to find the dynamical system induced by a projection which lead to quite distinct numerical approximations. One of these is developed further as we describe various ways in which knowledge of the full dynamical system can be incorporated into the approximate projected system. The ideas of the paper are illustrated in some more or less simple examples, which range from a simple system of nonlinear ODEs which have an attracting limit cycle, to low-dimensional solutions of the Kuramoto–Sivashinsky equation which need many Galerkin modes for their description.

Key Words

reduced dynamical systems secant projections 

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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  1. 1.Department of MathematicsUMISTManchesterU.K.
  2. 2.Department of MathematicsColorado State UniversityFort CollinsU.S.A.

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