Spectral approach to logical distribution-free classification problem

A spectral approach to logical distribution-free classification is presented. The discriminant function is based on logical conjunctions which are called descriptors of the classes. The main steps of the algorithm are: (1) finding a minimal descriptor for each pattern class, (2) computing a local discriminant function for each minimal descriptor and (3) making the actual classification of the observed pattern into a class. For constructing minimal descriptors we utilize spectral algorithms to extract the prime implicants of the Boolean function corresponding: to a prototype class. The spectral algorithms involve computing Walsh and conjunctive (need-Muller) spectra for which there exists fast algorithms.