Publications:

M.J. Prerau, A.C. Smith, Y. Kubota, M. Yanike, W. Suzuki, A.M. Graybiel, E.N. Brown, Characterizing learning using continuous and discrete measures of performance, Journal of Neurophysiology, 2007, Submitted.

M.J. Prerau,  A.C. Smith, M. Yanike, W.A. Suzuki, E.N. Brown,  A mixed filter algorithm for cognitive state estimation from simultaneously recorded  continuous-valued and binary measures of performance, Biological Cybernetics, 2007, Submitted.

M.J. Prerau, U.T. Eden, Beyond the Gaussian: A Bayesian framework using empirical distributions for the analysis of differential firing in hippocampal place cells. Society for Neuroscience abstract, 2006.

M.J. Prerau, Y. Kubota, A.M. Graybiel, A.C. Smith, E.N. Brown, Estimating learning from simultaneously recorded continuous and discrete measures, Society for Neuroscience Abstract, 2004.

C.D. Salzman, M.J. Prerau, M.A. Belova, J.J. Paton, A.C. Smith, E.N. Brown, Bias estimation using dynamic estimation on binary measures of performance, Society for Neuroscience Abstract, 2004.

M.J. Prerau,  Who  could ask for anything more? Mixed modality rhythmic discrimination aptitude in human subjects, Proceedings of the International Conference on Music Perception and Cognition, April 2004. [Postscript, PDF]

E. Eskin, A. Arnold, M. Prerau, L. Portnoy, S. Stolfo, 2002. A geometric framework for unsupervised anomaly detection: detecting intrusions in unlabeled data. In: D. Barbara, S. Jajodia, (Eds.), Applications of Data Mining in Computer Security, Kluwer, Dordrecht, ISBN 1-4020-7054-3 (Chapter 4). [Postscript, PDF]

M.J. Prerau,  On the possibilities of an analytic synthesis system,  Proceedings of the European Conference on Artificial Life 2001 Workshop: Artificial Life Models for Musical Applications. Prague, Czech Republic, September 2001. [PDF]

Other Works:

Michael Prerau. Unsupervised Anomaly Detection Using an Optimized K-Nearest Neighbors Algorithm. Undergraduate Thesis. To be submitted for publication.

[Postscript, PDF]

Michael Prerau. Slow Motion Sound: Implementing Time Compression/Expansion with a Phase Vocoder. Project for Fourier Analysis class.

[Postscript, PDF]