Using Genetic Algorithms to Improve the Initial Weights of SOM Network in the Musical Instrument Classification
利用遗传算法改进SOM网络初始权值的乐器分类

For the problem of excessive training and easy to fall into local minimum in SOM network in the classification caused by the randomness of its initial weight, using genetic algorithm to improve network initial weights in instrument classification is proposed. Simulation experiments extract 12-order MFCC coefficients of 10 different kinds of musical instruments. Then use the genetic algorithm to calculate the fitness value of each order in each instrument, and use the fitness value as the network initial weights. Simulation results show that： the way of using genetic algorithms to improve the initial weights of SOM network in the musical instrument classification is effective and the classification accuracy can reach 83.51%.