IEEE Transactions on Computers
Recognition of Waveforms Using Autoregressive Feature Extraction
IEEE Transactions on Computers
Feature Evalution with Measures of Probabilistic Dependence
IEEE Transactions on Computers
The Application of Filtered Transforms to the General Classification Problem
IEEE Transactions on Computers
Image Data Processing by Hadamard-Haar Transform
IEEE Transactions on Computers
A Set of Invariants Within the Power Spectrum of Unitary Transformations
IEEE Transactions on Computers
A hybrid approach based on DCT-Genetic-Fuzzy inference system for speech recognition
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
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An important aspect in mathematical pattern recognition is the usually noninvertible transformation from the pattern space to a reduced dimensionality feature space that allows a classification process to be implemented on a reasonable number of features. Such feature-selecting transformations range from simple coordinate stretching and shrinking to highly complex nonlinear extraction algorithms. A class of feature-selection transformations to which this note addresses itself is that given by multidimensional rotations. Unitary transformations of particular interest are the Karhunen-Loeve, Fourier, Hadamard or Walsh, and the Haar transforms. A character recognition experiment is selected for exemplary purposes and the use of features in the rotated spaces results in effective minimum distance classification.