In this paper an automated method to recognize the musical instruments playing the musical signals is presented. Various features of the musical instruments and musical signals are investigated. The features can broadly be grouped into three categories: temporal, spectral, and cepstral features. A composite neural network structure is proposed as the classifier. The performance of the composite neural network using a set of carefully chosen features is compared with that of the traditional neural network. Experimental results show that the accuracy achieved using composite structure (94%) is significantly higher than that using the traditional structure (88%) when more than four musical instruments are to be distinguished.