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Tackling the Inverse Problem for Non-Autonomous Systems

Application to the Life Sciences

  • Book
  • © 2014

Overview

Authors:
  1. Tomislav Stankovski

    1. Department of Physics, Lancaster University, Lancaster, United Kingdom

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  • Nominated as an outstanding Ph.D. thesis by the University of Lancaster, UK
  • Describes a new inference technique for time-evolving coupled systems in the presence of noise
  • Includes the first reconstruction of a time-evolving coupling function between open (biological) systems
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Theses (Springer Theses)

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-xv
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  2. Introduction

    • Tomislav Stankovski
    Pages 1-8

  3. Theoretical Background: Non-Autonomous Systems and Synchronization

    • Tomislav Stankovski
    Pages 9-35

  4. Bayesian Inference of Time-Evolving Coupled Systems in the Presence of Noise

    • Tomislav Stankovski
    Pages 37-74

  5. Application to Life Sciences

    • Tomislav Stankovski
    Pages 75-108

  6. Analogue Simulation and Synchronization Analysis of Non-Autonomous Oscillators

    • Tomislav Stankovski
    Pages 109-117

  7. Conclusion

    • Tomislav Stankovski
    Pages 119-122

  8. Back Matter

    Pages 123-135
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Keywords

About this book

This thesis presents a new method for following evolving interactions between coupled oscillatory systems of the kind that abound in nature. Examples range from the subcellular level, to ecosystems, through climate dynamics, to the movements of planets and stars.  Such systems mutually interact, adjusting their internal clocks, and may correspondingly move between synchronized and non-synchronized states. The thesis describes a way of using Bayesian inference to exploit the presence of random fluctuations, thus analyzing these processes in unprecedented detail.  It first develops the basic theory of interacting oscillators whose frequencies are non-constant, and then applies it to the human heart and lungs as an example. Their coupling function can be used to follow with great precision the transitions into and out of synchronization. The method described has the potential to illuminate the ageing process as well as to improve diagnostics in cardiology, anesthesiology and neuroscience, and yields insights into a wide diversity of natural processes.

Authors and Affiliations

  • Department of Physics, Lancaster University, Lancaster, United Kingdom

    Tomislav Stankovski

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