Across cultures, and between individuals, certain musical pieces are consistently rated more favourably than others and the mathematical analysis of musical perception has a long history. We find that musical scores which are widely perceived to be "good" generate complex networks with certain invariant properties: scale-free networks with strong clustering of nodes within the network.

We describe a method to generate random musical compositions from these networks (essentially, as a weighted random walk on the network) and find that scores generated in this manner are also perceived to be reasonably "good" and are similar (in the network statistical sense) to the specific score from which the generating network was produced. We will also introduce the concept of "motifs" in music and in networks. Creating and incorporating motifs in our network-based computer composition has shown to produce "appealing" music. We will construct networks for selected works from the late Chinese pop singer Teresa Teng, and use the constructed networks for recomposing music that mimicks the classic Teng's style.

The Speaker:
Michael Tse graduated from Melbourne University, Australia, with BEng(Hons) and PhD degrees. both in electrical engineering. He is presently a Chair Professor with the Department of Electronic and Information Engineering at HK PolyU. His research interests include power electronics, communication networks, and nonlinear systems. Dr. Tse is a Fellow of IEEE and a Fellow of IE Australia. His website is http://cktse.eie.polyu.edu.hk.

* ALL ARE WELCOME
Contact : Prof. George Baciu
Email : csgeorge@comp.polyu.edu.hk
Tel : 2766-7295 or 2766-7272