Giuliano Simoncelli

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In this paper, we use Hidden Markov Models (HMMs) for abstracting the style of a composer and for recognizing it out of an unknown excerpt. We employed a data set of 605 musical themes written by five well-known composers (Mozart, Beethoven, Dvorak, Stravinsky, Beatles). A preliminary investigation based on descriptive statistics served the purpose of(More)
“Neuronic” or “decision equations”, first proposed as a mathematical model of neural activity, have shown, after their exact, compact solution was found, typical behaviours that make them natural tools for General Systems studies. It is shown here that their mathematical investigation is remarkably furthered by generalizing the “triangular inequality” to(More)
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