[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Predictive Information in Gaussian Processes with Application to Music Analysis

  • Conference paper
Geometric Science of Information (GSI 2013)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8085))

Included in the following conference series:

  • 4967 Accesses

Abstract

We describe an information-theoretic approach to the analysis of sequential data, which emphasises the predictive aspects of perception, and the dynamic process of forming and modifying expectations about an unfolding stream of data, characterising these using a set of process information measures. After reviewing the theoretical foundations and the definition of the predictive information rate, we describe how this can be computed for Gaussian processes, including how the approach can be adpated to non-stationary processes, using an online Bayesian spectral estimation method to compute the Bayesian surprise. We finish with a sample analysis of a recording of Steve Reich’s Drumming.

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

Access this chapter

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 35.99
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
GBP 44.99
Price includes VAT (United Kingdom)
  • Compact, lightweight 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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Crutchfield, J., Packard, N.: Symbolic dynamics of noisy chaos. Physica D: Nonlinear Phenomena 7, 201–223 (1983)

    Article  MathSciNet  Google Scholar 

  2. Grassberger, P.: Toward a quantitative theory of self-generated complexity. International Journal of Theoretical Physics 25, 907–938 (1986)

    Article  MathSciNet  MATH  Google Scholar 

  3. Bialek, W., Nemenman, I., Tishby, N.: Predictability, complexity, and learning. Neural Computation 13, 2409–2463 (2001)

    Article  MATH  Google Scholar 

  4. Abdallah, S.A., Plumbley, M.D.: Information dynamics: Patterns of expectation and surprise in the perception of music. Connection Science 21, 89–117 (2009)

    Article  Google Scholar 

  5. Abdallah, S.A., Plumbley, M.D.: A measure of statistical complexity based on predictive information with application to finite spin systems. Physics Letters A 376, 275–281 (2012)

    Article  MATH  Google Scholar 

  6. Dubnov, S.: Spectral anticipations. Computer Music Journal 30, 63–83 (2006)

    Article  Google Scholar 

  7. Verdú, S., Weissman, T.: Erasure entropy. In: IEEE International Symposium on Information Theory (ISIT 2006), pp. 98–102 (2006)

    Google Scholar 

  8. Yeung, R.: A new outlook on Shannon’s information measures. IEEE Transactions on Information Theory 37, 466–474 (1991)

    Article  MathSciNet  MATH  Google Scholar 

  9. James, R.G., Ellison, C.J., Crutchfield, J.P.: Anatomy of a bit: Information in a time series observation. Chaos 21, 037109 (2011)

    Article  Google Scholar 

  10. Itti, L., Baldi, P.: Bayesian surprise attracts human attention. In: Advances Neural in Information Processing Systems (NIPS 2005), vol. 19, pp. 547–554. MIT Press, Cambridge (2005)

    Google Scholar 

  11. Abdallah, S.A., Plumbley, M.D.: Instantaneous predictive information in Gaussian processes. Unpublished Technical Note (2012)

    Google Scholar 

  12. Kitagawa, G., Gersch, W.: A smoothness priors time-varying ar coefficient modeling of nonstationary covariance time series. IEEE Transactions on Automatic Control 30, 48–56 (1985)

    Article  MathSciNet  MATH  Google Scholar 

  13. Dubnov, S., McAdams, S., Reynolds, R.: Structural and affective aspects of music from statistical audio signal analysis. Journal of the American Society for Information Science and Technology 57, 1526–1536 (2006)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Abdallah, S., Plumbley, M. (2013). Predictive Information in Gaussian Processes with Application to Music Analysis. In: Nielsen, F., Barbaresco, F. (eds) Geometric Science of Information. GSI 2013. Lecture Notes in Computer Science, vol 8085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40020-9_72

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-40020-9_72

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40019-3

  • Online ISBN: 978-3-642-40020-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics