A. Yu. Dorogov

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In the paper, the use of neural networks for the implementation of fast algorithms of spectral transformations is discussed. It is shown that the fast algorithms are particular cases of fast neural networks (FNNs). Methods for parametric tuning FNNs to a given system of basis functions are suggested. Neural network implementations of the fast Walsh and(More)
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(More)
Data system analysis methods for designing of collective neural network classifiers are considered. It is suggested to use methods of sign graph local balancing and algorithms of system behavior stereotype selection for construction of competent areas of local classifiers. Connection graph is formed on the base of statistic dependences between variables of(More)
The proposed localization method for graphical objects of scene image is invariant to the illuminance conditions, scale, offset and rotation of the objects. The method is based on a vector representation of scene image and searched object. Model for building of object pattern and algorithm of its recognition are represented. Experimental results for real(More)
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