Image recognition with fuzzy ADALINE neurons

Author

Paul, B. ; Konar, A. ; Mandal, A.K.

Author_Institution

Dept. of Electron. & Telecommun. Eng., Jadavpur Univ., Calcutta, India

Volume

1

fYear

1998

fDate

4-8 May 1998

Firstpage

747

Abstract

The paper aims at extending the scope of application of Widrow-Hoff´s ADALINE model from binary to gray level (fuzzy) pattern recognition. The condition of stability for the extended ADALINE model is derived, and the algorithm for training the multilayer feedforward neural net consisting of ADALINE neurons is presented. The time required for training the neural net is insignificantly small. The scheme for the recognition of objects from their gray level images using the fuzzy ADALINE model is translation, rotation and size invariant

Keywords

feedforward neural nets; fuzzy neural nets; learning (artificial intelligence); object recognition; Widrow-Hoff; binary to gray level images; fuzzy ADALINE neurons; learning algorithm; multilayer feedforward neural net; pattern recognition; recognition recognition; Biomedical signal processing; Image recognition; Linearity; Multi-layer neural network; Neural networks; Neurons; Pattern recognition; Retina; Signal processing algorithms; Stability;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7576

Print_ISBN

0-7803-4859-1

Type

conf

DOI

10.1109/IJCNN.1998.682374

Filename

682374