Referenced Items are not available for this document.
In this paper we show how polynomial cellular neural networks can be used to find new properties of two-dimensional binary cellular automata (CA). In particular, we define formally a complexity index for totalistic and semi-totalistic CA, and we discuss on the intrinsic complexity of universal CA finding a surprising result: universal rules are slightly more complex than linearly separable ones.
Published in:
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Date of Conference: 14-19 June 2009
- Page(s):
- 2459 - 2466
- ISSN :
- 1098-7576
- E-ISBN :
- 978-1-4244-3553-1
- Print ISBN:
- 978-1-4244-3548-7
- INSPEC Accession Number:
- 10802630
- Conference Location :
- Atlanta, GA
- Digital Object Identifier :
- 10.1109/IJCNN.2009.5178977
- Product Type:
- Conference Publications
About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
