Recommended books about computer generated music:

• Music and Connectionism / Peter M. Todd (Editor), D. Gareth Loy (Editor) / Hardcover / Published 1991.
• Musical networks : Parallel Distributed Perception and Performance / Niall Griffith (Editor), Peter M. Todd (Editor) / Hardcover / Published 1998.
• Computers and Musical Style / David Cope / Hardcover / Published 1991.
• Experiments in Musical Intelligence / David Cope / Paperback / Published 1996.

• Zurada: Introduction to Artificial Neural Systems.
• Bishop: Neural Networks for Pattern Recognition.
• Hertz, Krogh, and Palmer: Introduction to the Theory of Neural Computation.
• Haykin: Neural Networks: A Comprehensive Foundation.
• Faucett: Fundamentals of Neural Networks: Architectures, Algorithms And Applications.

• http://midiworld.com/cmc/index.htm – A well designed MIDI archive site of classical music, including almost every classical composer you can think about. Very recommended.
• http://www2.iicm.edu/Cpub – GN MIDI Solutions (Guenter Nagler's site), with free and ShareWare MIDI utilities (including C++ sources) and original compositions (I really like his compositions).
• http://www.csis.ul.ie/staff/niallgriffith – Niall Griffith’s Home Page, with bibliography of articles related to Musical Networks.
• http://www-ccrma.stanford.edu/~dang/ – Dan Gang's Home Page, where you can find his articles and more information.
• http://www.computermusic.org/ – International Computer Music Association.
• http://boethius.music.ucsb.edu/smt-list/smthome.html – The Society for Music Theory.
• http://mitpress.mit.edu/e-journals/Computer-Music-Journal/ – Computer Music Journal Home Page.
• Shareware Music Machine – The World's Biggest Music Software Site.
• http://www.harmony-central.com/ – Harmony Central®.
• http://www.ee.umd.edu/~blj/algorithmic_composition/ – Algorithmic Composition.
• http://www.oz.net/~cyu/Thesis.html – Computer Generated Music Composition.
• http://www.asahi-net.or.jp/~HB9T-KTD/music/muslnk2e.html – A list of Automated Composing Sites.

• ftp://ftp.sas.com/pub/neural/FAQ.html – Neural Network FAQ, including answers to every possible question you could have about Neural Networks, including a full list of available free or commercial software.
• http://www.mathworks.com/products/matlab/ – The MathWorks (the guys that brought you MATLAB) – MATLAB Introduction.
• http://www.emsl.pnl.gov:2080/proj/neuron/neural/homepage.html – Neural Networks at Pacific Northwest National Laboratory – a very good site with tons of links.
• http://diwww.epfl.ch/mantra/tutorial/english/index.html – Neural Java – Neural Networks Tutorial with Java Applets.
• http://www.shef.ac.uk/psychology/gurney/notes/download.html – Introduction to Neural Nets – an easy introduction from the psychology department at sheffield university (in postscript).
• http://www.faqs.org/faqs/ai-faq/neural-nets/part4/section-1.html – Books and articles about Neural Networks – a comprehensive survey of ANN related publications.
• http://www.ewh.ieee.org/tc/nnc/ – IEEE Neural Network Council Home Page
• http://www.inns.org/nn.html – INNS: Neural Networks – the official journal of the international neural network society.
• http://www.mathworks.com/access/helpdesk/help/pdf_doc/nnet/nnet.pdf – MATLAB’s Neural Network Toolbox User’s Guide (in PDF format).

(a full list of available free or commercial software can be found at the Neural Network FAQ site).

• MATLAB.
• PLANET.
• SNNS.
• ASPIRIN.
• aiNet.
• Nevada Back-propagation (NevProp).

(a full bibliography about musical Neural Networks can be found at Niall Griffith’s site).

• Akarte, N.J. (1992) Music Composition Using Neural Networks. Master's thesis, University of Nevada, Reno.
• Berger, J. & Gang, D. (1996) Modeling musical expectations: A neural network model of dynamic changes of expectation in the audition of functional tonal music. In Proceedings of the Fourth International Conference on Music Perception and Cognition (pp. 373-378). Montreal: McGill University, Faculty of Music.
• Berger, J. & Gang, D. (1997) A neural network model of metric perception and cognition in the audition of functional tonal music. In Proceedings of the 1997 International Computer Music Conference (pp. 23-26). San Francisco: International Computer Music Association.
• Calvert, D. & Stacey, D. (1991) Neural based methods for music composition. In International Joint Conference on Neural Networks (Vol. 2, p. 918). New York: IEEE.
• Drago, G.P., Martini, C., Morando, M. & Ridella, S. (1992) A high performance music composer based on a modified Jordan network. In The Fifth Italian Workshop on Neural Nets, WIRN VIETRI-92 (pp. 280- 285). Singapore: World Scientific.
• Drago, G.P., Martini, C., Morando, M. & Ridella, S. (1992) A neural network for music composition. In M.H. Hamza (Ed.), Proceedings of the Tenth IASTED International Conference (pp. 211-214). Zurich: Acta Press.
• Fedor, P. (1992) Principles of the design of D-neuronal networks I: Net representation for computer simulation of a melody compositional process. International Journal of Neural Systems, 3(1), 65-73.Freisleben, B. (1992) The neural composer: A network for musical applications. In Proceedings of the 1992 International Conference on Artificial Neural Networks(Vol. 2, pp. 1663-1666). Amsterdam: Elsevier.
• Fedor, P. (1992) Principles of the design of D-neuronal networks II: Composing simple melodies. International Journal of Neural Systems, 3(1), 75-82.
• Freisleben, B. (1992) The neural composer: A network for musical applications. In Proceedings of the 1992 International Conference on Artificial Neural Networks (Vol. 2, pp. 1663-1666). Amsterdam: Elsevier.
• Gang, D. & Berger, J. (1996) Modeling the degree of realized expectation in functional tonal music: A study of perceptual and cognitive modeling using neural networks. In D. Rossiter (Ed.), Proceedings of the 1996 International Computer Music Conference (pp. 454-457). San Francisco: International Computer Music Association.
• Gang, D. & Lehmann, D. (1995) An artificial neural net for harmonizing melodies. In E. Michie (Ed.), Proceedings of the 1995 International Computer Music Conference (pp. 440-447). San Francisco: International Computer Music Association.
• Gang, D., Lehmann, D. & Wagner, N. (1997) Harmonizing melodies in real-time: The connectionist approach. In Proceedings of the 1997 International Computer Music Conference (pp. 27-31). San Francisco: International Computer Music Association.
• Gibson, P.M. & Byrne, J.A. (1991) NEUROGEN: Musical composition using genetic algorithms and cooperating neural networks. In Proceedings of the Second International Conference on Artificial Neural Networks (pp. 309-313). IEE.
• Goldman, C., Gang, D., Rosenschein, J. & Lehmann, D. (1996) NETNEG: A hybrid interactive architecture for composing polyphonic music in real time. In D. Rossiter (Ed.), Proceedings of the 1996 International Computer Music Conference (pp. 133-140). San Francisco: International Computer Music Association.
• Horner, A. & Goldberg, D.E. (1991) Genetic algorithms and computer-assisted music composition. In B. Alphonce & B. Pennycock (Eds.), Proceedings of the 1991 International Computer Music Conference (pp. 479-482). San Francisco: International Computer Music Association.
• Kohonen, T., Laine, P., Tiits, K. & Torkkola, K. (1991) A nonheuristic automatic composing method. In P.M. Todd & D.G. Loy (Eds.), Music and Connectionism (pp. 229-242). Cambridge, MA: MIT Press.
• Laske, O. (1990) Letter: Connectionist composition. Computer Music Journal, 14(2), 11-12. Also in P.M. Todd & D.G. Loy (Eds.) (1991) Music and Connectionism (p. 260). Cambridge, MA: MIT Press.
• Lee, M. & Wessel, D. (1992) Connectionist models for real-time control of synthesis and compositional algorithms. In Proceedings of the 1992 International Computer Music Conference (pp. 277-280). San Francisco: International Computer Music Association.
• Lewis, J.P. (1989) Algorithms for music composition by neural nets: Improved CBR paradigms. In Proceedings of the 1989 International Computer Music Conference (pp. 180-183). San Francisco: International Computer Music Association.
• Lewis, J.P. (1991) Creation by refinement and the problem of algorithmic music composition. In P.M Todd. & D.G. Loy (Eds.), Music and Connectionism (pp. 212-228). Cambridge, MA: MIT Press.
• Mozer, M.C. (1991) Connectionist music composition based on melodic, stylistic, and psychophysical constraints. In P.M. Todd & D.G. Loy (Eds.), Music and Connectionism (pp. 195-211). Cambridge, MA: MIT Press.
• Mozer, M.C. & Soukup, T. (1991) Connectionist music composition based on melodic and stylistic constraints. In R. Lippmann, J. Moody & D. Touretzky (Eds.), Advances in Neural Information Processing Systems 3 (pp. 789-796). San Mateo, CA: Morgan Kaufmann.
• Nishijima, M. & Watanabe, K. (1992) Interactive music composer based on neural networks. In Proceedings of the 1992 International Computer Music Conference (pp. 53-56). San Francisco: International Computer Music Association.
• Riedmiller, M., and H. Braun, "A direct adaptive method for faster back-propagation learning: The RPROP algorithm," Proceedings of the IEEE International Conference on Neural Networks, San Francisco, 1993, pp. 586-591.
• Thywissen, K. (1997) Evolutionary based algorithmic composition: A demonstration of recent developments in genotator. In Proceedings of the 1997 International Computer Music Conference (pp. 368-371). San Francisco: International Computer Music Association.
• Todd, P.M. (1991) A connectionist approach to algorithmic composition. Computer Music Journal, 13(4), 27-43. Also in P.M. Todd & D.G. Loy (Eds.) (1991) Music and Connectionism (pp. 173-189). Cambridge, MA: MIT Press.
• Uno, Y. & Mozer, M.C. (1997) Neural net architectures in modeling compositional syntax: Prediction and perception of continuity in minimalist works by Phillip Glass & Louis Andriessen. In Proceedings of the 1997 International Computer Music Conference (pp. 129-132). San Francisco: International Computer Music Association.

Speedy