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Understanding chaotic dissipative dynamics in the State Space with Fuzzy Systems

Record type: Conference or Workshop Item (Other)

The introduction gives an overview of chaotic dynamics and their particular properties. The information theoretical approach of unbiased guess, which was proposed by Jaynes, is utilized to derive a probability distribution in the state space. The weighting of parts in the state space by fuzzy sets provides additional information which enables a "reconstruction" of probabilities of crisp elements in state spaces without explicitely given crisp boxes and their attached probabilities, when the resolution of the fuzzy sets is fine enough. After summerizing some of the probabilistic quantities for the qualitative description of chaotic maps, a simple example of two fuzzy sets bounded by a crisp interval is employed to demonstrate by comparing the numerical results together with an analytical map, how this approach may be used to calculate probability densities, which are a basic quantity for chaos understanding.

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Citation

Schilhabel, T.E. and Harris, C.J. (1996) Understanding chaotic dissipative dynamics in the State Space with Fuzzy Systems At Int. Conference on Adaptive Computing in Engineering Design and Control '96.

More information

Published date: March 1996
Additional Information: Address: Plymouth
Venue - Dates: Int. Conference on Adaptive Computing in Engineering Design and Control '96, 1996-03-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250005
URI: http://eprints.soton.ac.uk/id/eprint/250005
PURE UUID: c44752e2-48d8-4e58-9584-86fc0ad2cd6a

Catalogue record

Date deposited: 04 May 1999
Last modified: 18 Jul 2017 10:44

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Contributors

Author: T.E. Schilhabel
Author: C.J. Harris

University divisions


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