On Feature Extraction Capabilities of Fast Orthogonal Neural Networks
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.
KeywordsRecognition Rate Multilayer Perceptron Linear Neural Network Error Recognition Rate Orthogonal Network
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- 1.Osowski, S.: Neural networks for information processing (in Polish). OWPW, Warsaw (2000)Google Scholar
- 3.Stasiak, B., Yatsymirskyy, M.: Application of Fourier-Mellin Transform To Categorization of 3D Objects (in Polish). In: Proc. of the III Conference on Information Technologies, Gdańsk, Poland (2005)Google Scholar
- 5.Pan, Z., Rust, A., Bolouri, H.: Image Redundancy Reduction for Neural Network Classification using Discrete Cosine Transforms. In: Proc. of the International Joint Conference on Neural Networks, Como, Italy, vol. 3, pp. 149–154 (2000)Google Scholar
- 6.Jacymirski, M., Szczepaniak, P.S.: Neural realization of fast linear filters. In: Proc. of the 4th EURASIP - IEEE Region 8 International Symposium on Video/Image Processing and Multimedia Communications, pp. 153–157 (2002)Google Scholar
- 9.Jacymirski, M.: Fast homogeneous algorithms of cosine transforms, type II and III with tangent multipliers (in Polish). In: Automatics, vol. 7, pp. 727–741. AGH University of Science and Technology Press, Cracow (2003)Google Scholar
- 10.Stasiak, B., Yatsymirskyy, M.: Recursive learning of fast orthogonal neural networks. In: Proc. of the International Conf. on Signals and Electronic Systems, pp. 653–656 (2006)Google Scholar
- 11.Rutkowski, L.: Methods and techniques of artificial intelligence (in Polish). Polish Scientific Publishers PWN, Warszawa (2005)Google Scholar
- 12.Hettich, S., Bay, S.D.: The UCI KDD Archive. University of California, Department of Information and Computer Science, Irvine, CA (1999), http://kdd.ics.uci.edu