Nasuto, S. ORCID: https://orcid.org/0000-0001-9414-9049, Bishop, M. J. and Lauria, S.
(1998)
Time complexity analysis of the stochastic diffusion search.
Neural Computation, 98.
Abstract/Summary
The Stochastic Diffusion Search algorithm -an integral part of Stochastic Search Networks is investigated. Stochastic Diffusion Search is an alternative solution for invariant pattern recognition and focus of attention. It has been shown that the algorithm can be modelled as an ergodic, finite state Markov Chain under some non-restrictive assumptions. Sub-linear time complexity for some settings of parameters has been formulated and proved. Some properties of the algorithm are then characterised and numerical examples illustrating some features of the algorithm are presented.
Item Type | Article |
URI | https://reading-clone.eprints-hosting.org/id/eprint/27177 |
Item Type | Article |
Refereed | Yes |
Divisions | Life Sciences > School of Biological Sciences > Department of Bio-Engineering |
Uncontrolled Keywords | Stochastic Diffusion, invariant pattern recognition, focus of attention, Markov Chains modelling, time complexity analysis |
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