Skip to main content
SpringerLink
Log in
Book cover

Proceedings of the Third International Conference on Soft Computing for Problem Solving pp 459–466Cite as

Reconstruction of Noisy Bezier Curves Using Artificial Neural Networks

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 258))

Abstract

The current work examines the reconstruction of Bezier curves with noisy data using artificial neural networks. Feed forward network with back propagation learning is used to fit the noisy data of the Bezier curves. Different parameters like learning rate, number of hidden layer neurons and number of epochs are studied and the results are compared for different runs. The best suited parameters are established for this specific problem.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • 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

Learn about institutional subscriptions

References

  1. Rogers, D.F., Adams, J.A.: Mathematical Elements of Computer Graphics. Tata Mc Graw Hill Publications, New Delhi (1990)

    Google Scholar 

  2. Uys, E.: An investigation into using neural networks for statistical classificationandre regression. University of Pretoria, Pretoria (2010)

    Google Scholar 

  3. Paliwal, Mukta, Kumar, Usha A.: Neural networks and statistical techniques: a review of applications. Expert Syst. Appl. 36(1), 2–17 (2009)

    Article  Google Scholar 

  4. Liu1, X., Huang, H., Xu, W.: Approximate B-Spline Surface Based on RBF Neural Networks. Lecture Notes in Computer Science, vol 3514, pp. 995–1002. Springer, Heidelberg (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. USICT, Guru Gobind Singh Indraprastha University, Delhi, India

    Kavita Khanna & Navin Rajpal

Authors
  1. Kavita Khanna
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Navin Rajpal
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kavita Khanna .

Editor information

Editors and Affiliations

  1. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Millie Pant

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  3. Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

  4. Department of Applied Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer India

About this paper

Cite this paper

Khanna, K., Rajpal, N. (2014). Reconstruction of Noisy Bezier Curves Using Artificial Neural Networks. In: Pant, M., Deep, K., Nagar, A., Bansal, J. (eds) Proceedings of the Third International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 258. Springer, New Delhi. https://doi.org/10.1007/978-81-322-1771-8_40

Download citation

  • DOI: https://doi.org/10.1007/978-81-322-1771-8_40

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-1770-1

  • Online ISBN: 978-81-322-1771-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation