Algorithms for Approximation

Proceedings of the 5th International Conference, Chester, July 2005

  • Armin Iske
  • Jeremy Levesley
Conference proceedings

DOI: 10.1007/978-3-540-46551-5

Table of contents (30 papers)

  1. Front Matter
    Pages I-XIII
  2. Imaging and Data Mining

    1. Front Matter
      Pages 1-1
    2. Ranking as Function Approximation
      Christopher J. C. Burges
      Pages 3-18
    3. Energy-Based Image Simplification with Nonlocal Data and Smoothness Terms
      Stephan Didas, Mrázek Pavel, Joachim Weickert
      Pages 51-60
    4. Multiscale Voice Morphing Using Radial Basis Function Analysis
      Christina Orphanidou, Irene M. Moroz, Stephen J. Roberts
      Pages 61-69
    5. Associating Families of Curves Using Feature Extraction and Cluster Analysis
      Jane L. Terry, Andrew Crampton, Chris J. Talbot
      Pages 71-80
  3. Numerical Simulation

  4. Statistical Approximation Methods

    1. Front Matter
      Pages 146-146
    2. Algorithms for Structured Gauss-Markov Regression
      Alistair B. Forbes
      Pages 167-185
    3. Uncertainty Evaluation in Reservoir Forecasting by Bayes Linear Methodology
      Daniel Busby, Chris L. Farmer, Armin Iske
      Pages 187-196
  5. Data Fitting and Modelling

    1. Front Matter
      Pages 198-198
    2. Integral Interpolation
      Rick K. Beatson, Michael K. Langton
      Pages 199-218

About these proceedings

Introduction

Approximation methods are vital in many challenging applications of computational science and engineering.

This is a collection of papers from world experts in a broad variety of relevant applications, including pattern recognition, machine learning, multiscale modelling of fluid flow, metrology, geometric modelling, tomography, signal and image processing.

It documents recent theoretical developments which have lead to new trends in approximation, it gives important computational aspects and multidisciplinary applications, thus making it a perfect fit for graduate students and researchers in science and engineering who wish to understand and develop numerical algorithms for the solution of their specific problems.

An important feature of the book is that it brings together modern methods from statistics, mathematical modelling and numerical simulation for the solution of relevant problems, with a wide range of inherent scales.

Contributions of industrial mathematicians, including representatives from Microsoft and Schlumberger, foster the transfer of the latest approximation methods to real-world applications.

Keywords

Alignment Markov Numerical integration Regression STATISTICA Signal algorithms data mining image processing metrology numerical methods numerical quadrature simulation statistics

Editors and affiliations

  • Armin Iske
    • 1
  • Jeremy Levesley
    • 2
  1. 1.Department MathematikUniversität HamburgHamburgGermany
  2. 2.Department of MathematicsUniversity of LeicesterLeicesterUK

Bibliographic information

  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-540-33283-1
  • Online ISBN 978-3-540-46551-5