On Feature Extraction Capabilities of Fast Orthogonal Neural Networks

Authors:
Bartłomiej Stasiak;Mykhaylo Yatsymirskyy
Affiliations:
Institute of Computer Science, Technical University of Łódź, ul. Wólczańska 215, 93-005 Łódź, Poland;Institute of Computer Science, Technical University of Łódź, ul. Wólczańska 215, 93-005 Łódź, Poland
Venue:
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
Year:
2007

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Abstract

The paper investigates capabilities of fast orthogonal neural networks in a feature extraction task for classification problems. Neural networks with an architecture based on the fast cosine transform, type II and IV are built and applied for extraction of features used as a classification base for a multilayer perceptron. The results of the tests show that adaptation of the neural network allows to obtain a better transform in the feature extraction sense as compared to the fast cosine transform. The neural implementation of both the feature extractor and the classifier enables integration and joint learning of both blocks.