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Frequency domain representation of two dimensional gray-level images is used to develop a pattern recognition method that is invariant to rotation, translation and scaling. Frequency domain representation is a natural feature detector that allows the use of only few directions of highest energy as training data for a set of Artiicial Neural Networks (ANNs).(More)
We present a new training rule for a single-layered linear network with complex valued weights and activation levels. This novel 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(More)
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