Dynamics Modeling of Musical String by ANN

• Main Authors: Liang, Sheng-Fu, 梁勝富
• Other Authors: Chin-Teng Lin, Alvin Su
• Format: Others
• Language: zh-TW
• Published: 1996
• Online Access: http://ndltd.ncl.edu.tw/handle/94418248270030414154

碩士 === 國立交通大學 === 控制工程系 === 84 === Music synthesis by physical modeling methods becomes the major research topic in the related area when FM synthesis and Wavetable synthesis cannot satisfy the demanding users. Combining the property of wave propagation and the associate discrete-time implementation, it is possible to generate realistic and dynamic musical tones. We first advance the Karplus-Strong plucked-string algorithm into a 2-D membrane extension. In order to model?sHeal instrument, we propose a class of neural network called Linear Scattering Recurrent Network (LSRN) which employs the measurement of the response of a string as the learning data such that the model can be trained to be a counterpart of the string in the synthesis domain. The correspondent learning algorithm and computer simulations are given to demonstrate the encouraging modeling results. Musical instrumental nonlinearity which points to our future works is also discussed.