[1] P. Scott, Music classification using neural networks, Manuscript Class ee373a, Stanford, (2001).
[2] J.-W. Lee, S.-B. Park, S.-K. Kim, Music genre classification using a time-delay neural network, in: Advances in Neural Networks-ISNN 2006, Springer, 2006, pp. 178-187.
[3] Z. Cataltepe, Y. Yaslan, A. Sonmez, Music genre classification using MIDI and audio features, EURASIP Journal on Advances in Signal Processing, 2007 (2007) 1-8.
[4] K. Kosina, Music genre recognition, (2002).
[5] H. Habibi, M. HomayoonPour, Automatic detection of music styles, Signal and Data Processing, 1 (2010) 33-52.
[6] N. Darabi, N. Azimi, H. Nojumi, Recognition of Dastgah and Maqam for Persian music with detecting skeletal melodic models, in: Proc. 2nd IEEE BENELUX/DSP Valley Signal Processing Symposium, Citeseer, 2006.
[7] S. Abdoli, Iranian traditional music Dastgah classification, in: ISMIR, 2011, pp. 275-280.
[8] M.A. Layegh, S. Haghipour, Y.N. Sarem, Classification of the Radif of Mirza Abdollah a canonic repertoire of Persian music using SVM method, Gazi University Journal of Science Part A: Engineering and Innovation, 1 (2013) 57-66.
[9] H. Hajimolahoseini, R. Amirfattahi, M. Zekri, Real-time classification of Persian musical Dastgahs using artificial neural network, in: 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP), IEEE, 2012, pp. 157-160.
[10] S. Mahmoodan, A. Banooshi, Automatic classification of Iranian music by an artificial neural network, in: 2nd International Conference on Acoustics and Vibration, 2012.
[11] N. Darabi, Generation and analyzation digital signals of music and automatic recognition of music styles, M.Sc. Thesis, K. N. Toosi University of Technology, 2004.
[12] H. Farhat, The Dastgah concept in Persian music, Cambridge University Press, 2004.
[13] C.J. Plack, A.J. Oxenham, R.R. Fay, Pitch: neural coding and perception, Springer Science & Business Media, 2006.
[14] J.G. Roederer, The physics and psychophysics of music: an introduction, Springer Science & Business Media, 2008.
[15] D.A. Ross, Being in time to the music, Cambridge Scholars Publishing, 2008.
[16] R. Lyon, S. Shamma, Auditory representations of timbre and pitch, in: Auditory computation, Springer, 1996, pp. 221-270.
[17] B. Yegnanarayana, Artificial neural networks, PHI Learning Pvt. Ltd., 2009.
[18] G. Tzanetakis, P. Cook, Musical genre classification of audio signals, IEEE transactions on Speech and Audio Processing, 10 (2002) 293-302.