IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v152y2021ics0960077921007803.html
   My bibliography  Save this article

A constructive theory of shape

Author

Listed:
  • García-Morales, Vladimir

Abstract

We formulate a theory of shape valid for objects of arbitrary dimension whose contours are path connected. We apply this theory to the design and modeling of viable trajectories of complex dynamical systems. Infinite families of qualitatively similar shapes are constructed giving as input a finite ordered set of characteristic points (landmarks) and the value of a continuous parameter κ∈(0,∞). We prove that all shapes belonging to the same family are located within the convex hull of the landmarks. The theory is constructive in the sense that it provides a systematic means to build a mathematical model for any shape taken from the physical world. We illustrate this with a variety of examples: (chaotic) time series, plane curves, space filling curves, knots and strange attractors.

Suggested Citation

  • García-Morales, Vladimir, 2021. "A constructive theory of shape," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).
  • Handle: RePEc:eee:chsofr:v:152:y:2021:i:c:s0960077921007803
    DOI: 10.1016/j.chaos.2021.111426
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077921007803
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2021.111426?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Kwang‐Rae Kim & Ian L. Dryden & Huiling Le & Katie E. Severn, 2021. "Smoothing splines on Riemannian manifolds, with applications to 3D shape space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(1), pages 108-132, February.
    2. Freeman Dyson, 2004. "A meeting with Enrico Fermi," Nature, Nature, vol. 427(6972), pages 297-297, January.
    3. Peter E. Jupp & John T. Kent, 1987. "Fitting Smooth Paths to Spherical Data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 36(1), pages 34-46, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Kwang‐Rae Kim & Ian L. Dryden & Huiling Le & Katie E. Severn, 2021. "Smoothing splines on Riemannian manifolds, with applications to 3D shape space," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(1), pages 108-132, February.
    2. Hanna, Martin S. & Chang, Ted, 2000. "Fitting Smooth Histories to Rotation Data," Journal of Multivariate Analysis, Elsevier, vol. 75(1), pages 47-61, October.
    3. Meisam Moghimbeygi & Mousa Golalizadeh, 2019. "A longitudinal model for shapes through triangulation," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(1), pages 99-121, March.
    4. Schreiber, Michael, 2013. "How relevant is the predictive power of the h-index? A case study of the time-dependent Hirsch index," Journal of Informetrics, Elsevier, vol. 7(2), pages 325-329.
    5. Beran, Rudolf, 2016. "Nonparametric estimation of trend in directional data," Stochastic Processes and their Applications, Elsevier, vol. 126(12), pages 3808-3827.
    6. Valerio Varano & Stefano Gabriele & Franco Milicchio & Stefan Shlager & Ian Dryden & Paolo Piras, 2022. "Geodesics in the TPS Space," Mathematics, MDPI, vol. 10(9), pages 1-20, May.
    7. Samir, Chafik & Adouani, Ines, 2019. "C1 interpolating Bézier path on Riemannian manifolds, with applications to 3D shape space," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 371-384.
    8. Edward E. Rigdon, 2013. "Lee, Cadogan, and Chamberlain: an excellent point . . . But what about that iceberg?," AMS Review, Springer;Academy of Marketing Science, vol. 3(1), pages 24-29, March.
    9. Ian L. Dryden & Kwang-Rae Kim & Huiling Le, 2019. "Bayesian Linear Size-and-Shape Regression with Applications to Face Data," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 83-103, February.
    10. Greg Jensen & Fabian Muñoz & Yelda Alkan & Vincent P Ferrera & Herbert S Terrace, 2015. "Implicit Value Updating Explains Transitive Inference Performance: The Betasort Model," PLOS Computational Biology, Public Library of Science, vol. 11(9), pages 1-27, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:152:y:2021:i:c:s0960077921007803. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.