Construction of the polygonal fuzzy neural network and its approximation based on K-integral norm

Title:

Construction of the polygonal fuzzy neural network and its approximation based on K-integral norm

Creator:

Wang, Guijun and Li, Xiaoping

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:316ff1f8-4cfd-4af6-95f9-7a8f6c93bfd3
uuid:316ff1f8-4cfd-4af6-95f9-7a8f6c93bfd3
doi:10.14311/NNW.2014.24.021

Subject:

Polygonal fuzzy numbers, quasi-additive integral, integrable polygonal fuzzy valued functions, integral norm, polygonal fuzzy neural network, and universal approximation

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

The concept of an n-equidistant polygonal fuzzy number is introduced to avoid the complexity of the operations between fuzzy numbers. Firstly, the properties of linear operations and the convergence of n-equidistant polygonal fuzzy numbers are discussed, the method how to change a fuzzy number into an n-equidistant polygonal fuzzy number is shown. Next, for given a µ-integrable polygonal fuzzy valued function, an n-equidistant polygonal fuzzy valued function is constructed. By introducing the definition of K-quasi-additive integral and Kintegral norm, the universal approximation of polygonal fuzzy neural network are studied. The final result indicates that the polygonal fuzzy neural network still possess universal approximation to an integrable system.

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 | 2014 Volume:24 | Number:4

Harvested from:

CDK

Metadata only:

false