Search-space reductions in deriving a fractal set for an arbitrary shape

David John Nettleton; Roberto Garigliano

doi:10.1117/12.150581

1 September 1993 Search-space reductions in deriving a fractal set for an arbitrary shape

David John Nettleton, Roberto Garigliano

Proceedings Volume 1962, Adaptive and Learning Systems II; (1993) https://doi.org/10.1117/12.150581
Event: Optical Engineering and Photonics in Aerospace Sensing, 1993, Orlando, FL, United States

Abstract

At present the problem of finding a quick and efficient way of representing an arbitrary shape as a set of contraction mappings (an iterated function system) is unresolved. The main problem that arises is the sheer size and complexity of the search space. This paper examines several constraints that can be placed on solutions, each of which has a low computational complexity. These constraints considerably reduce the search space in which the solutions exist and can be used to aid a variety of search algorithms.

Citation Download Citation

David John Nettleton and Roberto Garigliano "Search-space reductions in deriving a fractal set for an arbitrary shape", Proc. SPIE 1962, Adaptive and Learning Systems II, (1 September 1993); https://doi.org/10.1117/12.150581

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available