Composer, Music Analysis Based On Complex Network And Auxiliary

Music is an art form which organizes the voice element with the objects shake rule. Music is the carrier of human mentality and emotion as well as the exist forms of community behavior. So, it is an important meaning in musical study. Along with the development of information technology, the numeric analyses and disposal of music turn into one of the hotspot in academe gradually. The domain primarily consists of musical classification, division, based on the content of the musical searches, musical intelligence and so on.This paper is combination of the complex network of music theory and studies the analyses and assistant composing. The main contents include the following aspects:Firstly, we study the correlation theory systemically. We model the musical information with complex networks. We discover the power-law distributing and small world characteristic. We can compose automated with the characteristics.Secondly, we analyze the Chinese ancient music and Western music with complex networks. With the characteristic of staff and GongChePu, we design a RT coding mode in order to pickup and change the information. We mine the motif of the music respectively and compare the characteristic indifferent cultures.Thirdly, we find the musical motif with data mining algorithm. The motifs exist in three forms:we find the motif with the method of motifs finding in complex networks to find out the frequent repeatedly musical; we use first-order derivative and second-order derivative to deal with the variation and developmental motifs; the trunk of the music is another representation. It often contains in front rhythm. We use the association rule mining algorithm to find out the trunk tone.Fourthly, on the base of musical characteristic with complex network, we bring forward a random walk algorithm for assistant composing. Base on the characteristic of nocturne, we design musical assistant and validate the correlation algorithm practically.