LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Zhao, Y.; Billings, S.A. (2005)
Publisher: Department of Automatic Control and Systems Engineering
Languages: English
Types: Book
Subjects:
Extracting the rules from spatio-temporal patterns generated by the evolution of Cellular Automata (CA) usually requires "a priori" information about the observed system, but in many applications little information will be known about the pattern. This paper introduces a new neighbourhood detection algorithm which can determine the range of the neighbourhood without any knowledge of the system by introducing a criterion based on Mutual Information (MI) and an indication of over-estimation. A coarse-to-fine identification routine is then proposed to determine the CA rule from the observed pattern. Examples, including data from a real experiment, are employed to evaluate the new algorithm.
  • No references.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article