A Generalized Technique for Spectral Analysis
IEEE Transactions on Computers
Fast orthogonal neural networks
ICAISC'06 Proceedings of the 8th international conference on Artificial Intelligence and Soft Computing
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A new method of learning fast one- and multiple-dimensional orthogonal transformations is considered. Tunable orthogonal transformations are regarded as special neural networks. The learning takes a finite number of steps. The learning algorithm does not have the error feedback and is absolutely stable. The method is based on fractal filtering of signals and images. Linguistic models are used to determine the topology and structure of fast transformations. Examples are given.