A Novel Fractional-Order Chaotic Phase Synchronization Model for Visual Selection and Shifting
release_untvu3y7rffvvchsh6ettw27hu
by
Xiaoran Lin, Shangbo Zhou, Hongbin Tang, Ying Qi, Xianzhong Xie
Abstract
Visual information processing is one of the fields of cognitive informatics. In this paper, a two-layer fractional-order chaotic network, which can simulate the mechanism of visual selection and shifting, is established. Unlike other object selection models, the proposed model introduces control units to select object. The first chaotic network layer of the model is used to implement image segmentation. A control layer is added as the second layer, consisting of a central neuron, which controls object selection and shifting. To implement visual selection and shifting, a strategy is proposed that can achieve different subnets corresponding to the objects in the first layer synchronizing with the central neuron at different time. The central unit acting as the central nervous system synchronizes with different subnets (hybrid systems), implementing the mechanism of visual selection and shifting in the human system. The proposed model corresponds better with the human visual system than the typical model of visual information encoding and transmission and provides new possibilities for further analysis of the mechanisms of the human cognitive system. The reasonability of the proposed model is verified by experiments using artificial and natural images.
In text/plain
format
Archived Files and Locations
application/pdf 14.2 MB
file_cqxoo4wddzatjigevsc263ggai
|
res.mdpi.com (web) web.archive.org (webarchive) |
application/pdf 14.2 MB
file_ydv3xhhxc5beta4mwhbemsasr4
|
web.archive.org (webarchive) pdfs.semanticscholar.org (aggregator) |
Open Access Publication
In DOAJ
In ISSN ROAD
In Keepers Registry
ISSN-L:
1099-4300
access all versions, variants, and formats of this works (eg, pre-prints)
Crossref Metadata (via API)
Worldcat
SHERPA/RoMEO (journal policies)
wikidata.org
CORE.ac.uk
Semantic Scholar
Google Scholar