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«ATTRACTOR NETWORK MODEL OF MUSIC TONALITY» 
Igor Yevin and Alexander Koblyakov

Опубликовано в: Синергетика и искусство

Igor Yevin and Alexander Koblyakov
Mechanical Engineering Institute, Russian Academy of Sciences

The attractor network model embodies the properties of an associative content-addressable memory. Every stored pattern (meaning or note) corresponds appropriate minimum on the potential function. Imprinting a pattern lowers its energy and the energy of all pattern in the vicinity. This creates a basin of attraction. Such system would be able to recognize inputting pattern which is pulled into one of the closest keypattern. Almost all familiar melodies are built around a central tone toward which the other tones gravitate and on which the melody usually ends. This central tone is the keynote, or tonic. Three stable steps of tonality: tonic, median, and dominant are keynotes or attractors of neural network model. Others steps of tonality play the role of recognizable patterns, gravitating to some or other keynote. Some recent experiments indicate that music possibly represents control of chaos in the brain and one may suggest that stable steps of tonalities are namely these tiny perturbations by which this control is realized.

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