Szczegóły publikacji
Opis bibliograficzny
Neurons can sort data efficiently / Adrian HORZYK // W: Artificial Intelligence and Soft Computing : 16th International Conference : ICAISC 2017 Zakopane, Poland, June 11–15, 2017 : proceedings, Pt. 1 / eds. Leszek Rutkowski, [et al.]. — Switzerland : Springer International Publishing, cop. 2017. — (Lecture Notes in Computer Science ; ISSN 0302-9743. Lecture Notes in Artificial Intelligence ; LNAI 10245). — Toż na Dysku Flash. — ISBN: 978-3-319-59062-2; e-ISBN: 978-3-319-59063-9. — S. 64–74. — Bibliogr. s. 73–74, Abstr.
Autor
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 106544 |
|---|---|
| Data dodania do BaDAP | 2017-06-28 |
| DOI | 10.1007/978-3-319-59063-9_6 |
| Rok publikacji | 2017 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Artificial Intelligence and Soft Computing 2017 |
| Czasopismo/seria | Lecture Notes in Computer Science |
Abstract
This paper introduces an efficient sorting algorithm that uses new models of receptors and neurons which apply the time-conditional approach characteristic for nervous systems. These models have been successfully applied to automatically construct neural graphs that consolidate representation of all sorted objects and relations between them. The introduced parallely working algorithm sorts objects simultaneously for all attributes constructing an active associative neural graph representing all sorted objects in linear time. The sequential version works in linear or sub-linearithmic time. The paper argues that neurons can be used for efficient sorting of objects and the constructed network can be further used to explore relationships between these objects.
