Skip to main content

Part of the book series: Biological and Medical Physics, Biomedical Engineering ((BIOMEDICAL))

Abstract

In this section two digital models evolved from biological cortical models will be presented. The first is the Pulse-Coupled Neural Network (PCNN) which for many years was the standard model for many image processing applications. The PCNN is based solely on the Eckhorn model but there are many other cortical models that exist. These models all have a common mathematical foundation, but beyond the common foundation each also had unique terms. Since the goal here is to build image processing routines and not to exactly simulate the biological system a new model was constructed. This model contained the common foundation without the extra terms and is therefore viewed as the intersection of several cortical models and it is named the Intersecting Cortical Model (ICM).

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas Lindblad .

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Lindblad, T., Kinser, J.M. (2013). The PCNN and ICM. In: Image Processing using Pulse-Coupled Neural Networks. Biological and Medical Physics, Biomedical Engineering. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36877-6_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-36877-6_4

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36876-9

  • Online ISBN: 978-3-642-36877-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics