Skip to main content

Optimal Mass Transport for Problems in Control, Statistical Estimation, and Image Analysis

  • Chapter
  • First Online:

Part of the book series: Operator Theory: Advances and Applications ((OT,volume 222))

Abstract

In this paper, we describe some properties of the Wasserstein-2 metric on the space of probability distributions of particular relevance to problems in control and signal processing. The resulting geodesics lead to interesting connections with Boltzmann entropy, heat equations (both linear and nonlinear), and suggest possible Riemannian structures on density functions. In particular, we observe similarities and connections with metrics originating in information geometry and prediction theory.

Mathematics Subject Classification. 34H05, 49J20.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Amari, S. and Nagaoka, H., Methods of Information Geometry, Memoirs of AMS 191, 2007.

    Google Scholar 

  2. S. Angenent, S. Haker, and A. Tannenbaum, “Minimizing flows for the Monge- Kantorovich problem,” SIAM J. Math. Analysis, vol. 35, pp. 61-97, 2003.

    Article  MathSciNet  MATH  Google Scholar 

  3. S. Angenent, G. Sapiro, and A. Tannenbaum, “On the affine invariant heat equation for nonconvex curves,” Journal of the American Mathematical Society 11 (1998), pp. 601-634.

    Article  MathSciNet  MATH  Google Scholar 

  4. J.-D. Benamou and Y. Brenier, “A computational fluid mechanics solution to the Monge-Kantorovich mass transfer problem,” Numerische Mathematik 84 (2000), pp. 375-393.

    Article  MathSciNet  MATH  Google Scholar 

  5. J.D. Benamou, “Numerical resolution of an unbalanced mass transport problem,” Mathematical Modeltíng and Numerical Analysis, 37(5), 851-862, 2003.

    Article  MathSciNet  MATH  Google Scholar 

  6. A. Figalli,"The optimal partial transport problem,” Archive for rational mechanics and analysis, 195(2): 533-560, 2010.

    Google Scholar 

  7. T. Georgiou, “Distances and Riemannian metrics for spectral density functions,” IEEE Trans. Signal Processing 55 (2007), pp. 3995-4004.

    MathSciNet  Google Scholar 

  8. T.T.Georgiou, J. Karlsson, and S. Takyar,“Metrics for power spectra: an axiomatic approach,” IEEE Trans. on Signal Processing, 57(3): 859-867, March 2009.

    Article  Google Scholar 

  9. R.M. Gray, A. Buzo, A.H. Gray, and Y. Matsuyama, “Distortion measures for speech processing,” IEEE Trans. on Acoustics, Speech, and Signal Proc., 28(4), pp. 367–376, 1980.

    Article  MATH  Google Scholar 

  10. X. Jiang, Z.Q. Luo and T.T. Georgiou, “Geometric Methods for Spectral Analysis,” IEEE Trans. on Signal Processing, to appear, 2012.

    Google Scholar 

  11. Xianhua Jiang, Lipeng Ning, and Tryphon T. Georgiou, “Distances and Riemannian metrics for multivariate spectral densities,” arXiv:1107.1345v1.

    Google Scholar 

  12. R. Jordan, D. Kinderlehrer, and F. Otto, “The variational formulation of the Fokker-Planck equation,” SIAM J. Math. Anal. 29 (1998), pp. 1-17.

    MathSciNet  MATH  Google Scholar 

  13. L.V. Kantorovich, “On a problem of Monge,” Uspekhi Mat. Nauk. 3 (1948), pp. 225-226.

    Google Scholar 

  14. P. Masani, “Recent trends in multivariable prediction theory,” in Krishnaiah, P.R., Editor, Multivariate Analysis, pp. 351–382, Academic Press, 1966.

    Google Scholar 

  15. D. McQuarrie, Statistical Mechanics (2nd edition), University Science Books, 2000.

    Google Scholar 

  16. S. Rachev and L. Rüschendorf, Mass Transportation Problems, Volumes I and II, Probability and Its Applications, Springer, New York, 1998.

    Google Scholar 

  17. C. Villani, Topics in Optimal Transportation, Graduate Studies in Mathematics, vol. 58, AMS, Providence, RI, 2003.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Emmanuel Tannenbaum .

Editor information

Editors and Affiliations

Additional information

This paper is dedicated to our dear friend and colleague, Professor Bill Helton on the occasion of his 65th birthday.

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer Basel

About this chapter

Cite this chapter

Tannenbaum, E., Georgiou, T., Tannenbaum, A. (2012). Optimal Mass Transport for Problems in Control, Statistical Estimation, and Image Analysis. In: Dym, H., de Oliveira, M., Putinar, M. (eds) Mathematical Methods in Systems, Optimization, and Control. Operator Theory: Advances and Applications, vol 222. Birkhäuser, Basel. https://doi.org/10.1007/978-3-0348-0411-0_22

Download citation

Publish with us

Policies and ethics