The learning algorithms of the GMDH neural network and their application to the medical image recognition

Author

Kondo, Tadashi

Author_Institution

Sch. of Med. Sci., Tokushima Univ., Japan

fYear

1998

fDate

29-31 Jul 1998

Firstpage

1109

Lastpage

1114

Abstract

In this paper, two types of the learning algorithms of the GMDH (group method of data handling) neural network are proposed. By using the heuristic self-organization method, the GMDH neural network can automatically organized the optimal neural network structure fit for the complexity of the nonlinear system. In the learning calculations, the neural network structure which is organized by the GMDH neural network is not changed and the values of the weights between the neurons are renewed. The GMDH neural network algorithm and its learning algorithms are applied to the medical image recognition

Keywords

heuristic programming; image recognition; learning (artificial intelligence); medical image processing; optimisation; self-organising feature maps; GMDH neural network; heuristic self-organization method; learning algorithms; medical image recognition; optimal neural network; Biomedical imaging; Equations; Image recognition; Input variables; Logistics; Multi-layer neural network; Neural networks; Neurons; Nonlinear systems; Regression analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE '98. Proceedings of the 37th SICE Annual Conference. International Session Papers

Conference_Location

Chiba

Type

conf

DOI

10.1109/SICE.1998.742987

Filename

742987