Welcome to the InfoSci Platform
Reference Hub26
Cognitively Inspired Neural Network for Recognition of Situations

Cognitively Inspired Neural Network for Recognition of Situations

Roman Ilin, Leonid Perlovsky
Copyright: © 2010 |Volume: 1 |Issue: 1 |Pages: 20
ISSN: 1947-928X|EISSN: 1947-9298|ISSN: 1947-928X|EISBN13: 9781616929961|EISSN: 1947-9298|DOI: 10.4018/jncr.2010010102
Cite Article Cite Article

MLA

Ilin, Roman, and Leonid Perlovsky. "Cognitively Inspired Neural Network for Recognition of Situations." IJNCR vol.1, no.1 2010: pp.36-55. http://doi.org/10.4018/jncr.2010010102

APA

Ilin, R. & Perlovsky, L. (2010). Cognitively Inspired Neural Network for Recognition of Situations. International Journal of Natural Computing Research (IJNCR), 1(1), 36-55. http://doi.org/10.4018/jncr.2010010102

Chicago

Ilin, Roman, and Leonid Perlovsky. "Cognitively Inspired Neural Network for Recognition of Situations," International Journal of Natural Computing Research (IJNCR) 1, no.1: 36-55. http://doi.org/10.4018/jncr.2010010102

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

The authors present a cognitively inspired mathematical learning framework called Neural Modeling Fields (NMF). They apply it to learning and recognition of situations composed of objects. NMF successfully overcomes the combinatorial complexity of associating subsets of objects with situations and demonstrates fast and reliable convergence. The implications of the current results for building multi-layered intelligent systems are also discussed.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.