Similarity-based heterogeneous neurons in the context of general observational models

Title:

Similarity-based heterogeneous neurons in the context of general observational models

Creator:

Valdés, Julio J.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:cc7dccdc-2f30-4ef1-9a88-28a270ba6943
uuid:cc7dccdc-2f30-4ef1-9a88-28a270ba6943

Subject:

general relatiorial structures, heterogeneous data, similarity functions, and heterogeneous neuron models

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

This paper preserits a framework for processing heterogeneous information based on the construction of general observational domains, and similarity-based function calculi sutable for data mining in domains which can be described by corresponding observational rnodels. These calculi are intuitive, sirnple, and sufřiciently general for classification and pattern recognition tasks. Functions in these calculi are represented by a particular kind of neuron rnodels and their behavior is illustrated with examples frorn real-world domains showing their capabilities in Processing heterogeneous, incornplete and fuzzy information.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2002 Volume:12 | Number:5

Harvested from:

CDK

Metadata only:

false