Title:

Modern approaches in fuzzy sets, intuitionistic fuzzy sets, generalized nets and related topics. Volume II: Applications * Generalized net model of slow learning algorithm of unsupervised art2 neural network

Subtitle:

Książka = Book ; KS/3/2014/T2R05

Creator:

Petkov, Todor ; Sotirov, Sotir

Publisher:

Instytut Badań Systemowych. Polska Akademia Nauk ; Systems Research Institute. Polish Academy of Sciences

Place of publishing:

Warszawa

Date issued/created:

2014

Description:

[3], 61-70 pages ; 21 cm ; Bibliography p. 70

Type of object:

Book/Chapter

Abstract:

This paper describes the slow learning algorithm of unsupervised adaptive resonance theory ART2 neural network. At first, the algorithm is presented step by step with formulas, and it is shown how an individual vector affects the network. At the end of the process, we have a learned network with stable recognition clusters according to the vectors. The process of the learning algorithm is presented by a generalized net model.

Relation:

Książka = Book

Resource type:

Text

Detailed Resource Type:

Book

Source:

KS-2014-03-T2R05

Language:

eng

Language of abstract:

eng

Rights:

Creative Commons Attribution BY 4.0 license

Terms of use:

Copyright-protected material. [CC BY 4.0] May be used within the scope specified in Creative Commons Attribution BY 4.0 license, full text available at: ; -

Digitizing institution:

Systems Research Institute of the Polish Academy of Sciences

Original in:

Library of Systems Research Institute PAS

Projects co-financed by:

Operational Program Digital Poland, 2014-2020, Measure 2.3: Digital accessibility and usefulness of public sector information; funds from the European Regional Development Fund and national co-financing from the state budget.

Access:

Open