Foundations of Computational Intelligence Volume 5

Function Approximation and Classification

  • Ajith Abraham
  • Aboul-Ella Hassanien
  • Václav Snášel

Part of the Studies in Computational Intelligence book series (SCI, volume 205)

Table of contents

  1. Front Matter
  2. Function Approximation and Classification: Theoretical Foundations

    1. Front Matter
      Pages 1-1
    2. Marcel Jiřina, Marcel Jiřina Jr.
      Pages 39-55
    3. Viviani Akemi Kasahara, Maria do Carmo Nicoletti
      Pages 57-78
    4. Renato Tinós, Luiz Otávio Murta Júnior
      Pages 127-145
  3. Function Approximation and Classification: Success Stories and Real World Applications

    1. Front Matter
      Pages 147-147
    2. Martín Gómez Ravetti, Regina Berretta, Pablo Moscato
      Pages 149-175
    3. André C. P. L. F. de Carvalho, Alex A. Freitas
      Pages 177-195
    4. Felix Bollenbeck, Udo Seiffert
      Pages 197-222
    5. Xinbo Gao, Bing Xiao, Dacheng Tao, Xuelong Li
      Pages 223-242
    6. Francisco Torrens, Gloria Castellano
      Pages 243-315
    7. Fernando Otero, Marc Segond, Alex A. Freitas, Colin G. Johnson, Denis Robilliard, Cyril Fonlupt
      Pages 339-357
    8. Marcel Jirina, Marcel Jirina Jr.
      Pages 359-376
  4. Back Matter

About this book

Introduction

Approximation theory is that area of analysis which is concerned with the ability to approximate functions by simpler and more easily calculated functions. It is an area which, like many other fields of analysis, has its primary roots in the mathematics.The need for function approximation and classification arises in many branches of applied mathematics, computer science and data mining in particular.

This edited volume comprises of 14 chapters, including several overview Chapters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of function approximation and classification. Besides research articles and expository papers on theory and algorithms of function approximation and classification, papers on numerical experiments and real world applications were also encouraged.

The Volume is divided into 2 parts: Part-I: Function Approximation and Classification – Theoretical Foundations and Part-II: Function Approximation and Classification – Success Stories and Real World Applications.

Keywords

Extension Function Approximation algorithm algorithms approximation theory classification computational intelligence data mining information system intelligence mathematics

Editors and affiliations

  • Ajith Abraham
    • 1
  • Aboul-Ella Hassanien
    • 2
  • Václav Snášel
    • 3
  1. 1.Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research ExcellenceWashingtonUSA
  2. 2.Faculty of Computers and Information, Information Technology DepartmentCairo UniversityOrman
  3. 3.Dept. Computer ScienceTechnical University OstravaOstravaCzech Republic

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-01536-6
  • Copyright Information Springer Berlin Heidelberg 2009
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Engineering
  • Print ISBN 978-3-642-01535-9
  • Online ISBN 978-3-642-01536-6
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • About this book