A complex valued Hebbian learning algorithm

Author

De Castro, Maria Cristina Felippetto ; De Castro, Fernando César C ; Amaral, José Nelson ; Franco, Paulo Roberto G

Author_Institution

Dept. of Electr. Eng., Univ. Catolica do Rio Grande do Sul, Porto Alegre, Brazil

Volume

2

fYear

1998

fDate

4-9 May 1998

Firstpage

1235

Abstract

We present a training rule for a single-layered linear network with complex valued weights and activation levels. This network can be used to extract the principal components of a complex valued data set. We also introduce a new training method that reduces the training time of the complex valued as well as of the real valued network. The use of the new network and training algorithm is illustrated with a problem of compressing images represented in the spectral domain

Keywords

Hebbian learning; data compression; image coding; neural nets; complex activation levels; complex valued Hebbian learning algorithm; complex valued data set; complex valued weights; image compression; principal components; real valued network; single-layered linear network; spectral domain; training rule; Data mining; Eigenvalues and eigenfunctions; Hebbian theory; Image coding; Neural networks; Neurons; Principal component analysis; Radar applications; Sonar; Vectors;

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.1998.685950

Filename

685950