首页> 外文会议>International Conference on Aritificial Neural Networks: Biological Inspirations(ICANN 2005) pt.1; 20050911-15; Warsaw(PL) >Chord Classifications by Artificial Neural Networks Revisited: Internal Representations of Circles of Major Thirds and Minor Thirds
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Chord Classifications by Artificial Neural Networks Revisited: Internal Representations of Circles of Major Thirds and Minor Thirds

机译:再谈人工神经网络的和弦分类:大三分和小三分之二的圆的内部表示

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摘要

This paper describes an artificial neural network that can be viewed as an extension of a pioneering network described by Laden and Keefe. This network was trained to classify sets of four musical notes into four different chord classes, regardless of the musical key or the form (inversion) of the chord. This new network has a slightly modified training set; after successful training the internal structure was analyzed and was found to be unique. That is, rather than using the 12 musical notes of Western music, the network used only 4 musical notes based upon circles of major thirds and of minor thirds.
机译:本文描述了一种人工神经网络,可以将其视为由Laden和Keefe描述的开拓性网络的扩展。对该网络进行了培训,可以将四个音符的集合分为四个不同的和弦类别,而与音乐键或和弦的形式(倒置)无关。这个新网络的训练集略有修改;成功训练后,内部结构经过分析,发现是独一无二的。也就是说,该网络没有使用西方音乐的12个音符,而是仅基于大三分之二和小三分之二的圈子使用了4个音符。

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