The musical source separation deals with extracting the musical signals from a mixture. To attain this goal, one of the efficient methods is to decompose the mixture into a dictionary of some basic functions that inherently describe the instruments. Usually, a unique function is synthesized for each of the notes of each instrument, called the note-specific atom. In this paper, a sine-harmonic model is utilized to synthesize note-specific atoms and the note’s fundamental frequency is used as a prior information to determine the model parameters. To calculate these parameters, the training signal spectrum is processed only around the main note harmonics. Experimental results demonstrated that the proposed method is much faster in note-specific atoms synthesis, without decreasing the source separation quality and can also eliminate the single-frequency noise from training signals.