Earlier Publications

2004

O'Dwyer, I J, Eriksen, H K, Wandelt, B D, Jewell, J B, Larson, D L, Górski, K M, Banday, A J, Levin, S, and Lilje, P B (2004). “Bayesian Power Spectrum Analysis of the First-Year Wilkinson Microwave Anisotropy Probe Data,” The Astrophysical Journal, 617(2), pp. L99–L102.

Jewell, Jeffrey, Levin, S, and Anderson, C H (2004). “Application of Monte Carlo Algorithms to the Bayesian Analysis of the Cosmic Microwave Background,” The Astrophysical Journal, 609(1), pp. 1–14.

Eriksen, H K, O'Dwyer, I J, Jewell, J B, Wandelt, B D, Larson, D L, Górski, K M, Levin, S, Banday, A J, and Lilje, P B (2004). “Power Spectrum Estimation from High-Resolution Maps by Gibbs Sampling,” The Astrophysical Journal Supplement Series, 155(2), pp. 227–241.

J. Pap, I. Ermolli, F. Gyorgi, and M. Turmon (2004). “Study of Solar Magnetic Feature Properties and Irradiance Variations,” 35th COSPAR Scientific Assembly.

T. M. Chin, J. B. Jewell, and M. Turmon (2004). “Phase Changes and State Estimation for Non-linear Systems,” Eos Trans. AGU, 85(47), Fall Meet. Suppl.. Abstract NG31B-0877.

M. Turmon (2004). “Symmetric Normal Mixtures,” Compstat 2004-Proceedings in Computational Statistics, pp. 1909-16, Physica-Verlag. Download (CL 04-1276).

2003

Li, P., Jacob, J., Braverman, A., and Block, G. (2003). “Visualization of Multi-dimensional MISR Datasets Using Self-Organizing Map,” AGU Fall Meeting Abstracts, pp. A165.

Siegel, H. and Li, P. (2003). “MSLT, Multi Surface Light Table, a Tool for Viewing Faults Under Their Terrain,” AGU Fall Meeting Abstracts, pp. B6.

M. Turmon, R. Granat, D. Katz, and J. Z. Lou (2003). “Tests and tolerances for High-Performance Software-Implemented Fault Detection,” IEEE Trans. Computers, pp. 579–591. Download (CL 02-0735).

2002

H.P. Jones, K.L. Harvey, J.M. Pap and D.G. Preminger, M. Turmon, and S.R. Walton (2002). “A comparison of feature classification methods for modeling solar irradiance variation,” 34th COSPAR Scientific Assembly.

J. Pap, H. Jones, M. Turmon, and L. Floyd (2002). “Study of the SOHO/VIRGO Irradiance Variations Using MDI and Kitt Peak Images,” Proc. SOHO-11 Workshop. ESA SP-508.

J. M. Pap, M. Turmon, L. Floyd, C. Frolich , and Ch. Wehrli (2002). “Total solar and spectral irradiance variations in solar cycles 21 to 23,” Adv. Space Res., 29, pp. 1923-1932.

M. Turmon, J. Pap, and S. Mukhtar (2002). “Statistical Pattern Recognition for Labeling Solar Active Regions: Application to SoHO/MDI Imagery,” Astrophysical Journal, 568(1), pp. 396-407. Download (CL 01-2847).

2001

Jewell, Jeffrey (2001). “A Statistical Characterization of Galactic Dust Emission as a Non-Gaussian Foreground of the Cosmic Microwave Background,” The Astrophysical Journal, 557(2), pp. 700–713.

E. Mjolsness, W. Fink, M. Turmon (2001). “Stochastic Parameterized Grammars for Bayesian Model Composition,” Interface-2001, Costa Mesa, CA.

M. Turmon (2001). “Mixture models for labeling scientific imagery,” Mixtures 2001: Recent Developments in Mixture Modeling, Hamburg.

2000

M. Turmon, R. Granat, and D. S. Katz (2000). “Software-Implemented Fault Detection for High-Performance Space Applications,” Proc. Intl. Conf. Dependable Systems and Networks, pp. 107–116. Download (CL 99-2014).

M. Turmon and R. Granat (2000). “Algorithm-Based Fault Tolerance for Spaceborne Computing: Basis and Implementations,” Proc. IEEE Aerospace Conference, pp. 411-420. Download (CL 00-0901).

1999

Jewell, Jeffrey, Lawrence, C R, and Levin, S (1999). “Bayesian Approach to Foreground Removal,” Microwave Foregrounds, vol. 181, p. 357.

M. Turmon, E. Mjolsness, V. Gluzman, and L. Ramsey (1999). “A Language for Probabilistic Modeling of Scientific Data,” Proc. Second Conf. Highly Structured Stochastic Systems, pp. 298–300, Pavia, Italy. Download (CL 99-1413, 00-1004).

1998

M. Turmon and S. Mukhtar (1998). “Representing Solar Active Regions with Triangulations,” Proc. Compstat-98, pp. 473-478, Bristol, UK. Download (CL 98-0761).

M. Turmon (1998). “Book review of <it>Machine Learning and Statistics</it>,” Jour. American Statistical Association, 93(442), pp. 833-834.

M. Turmon, J. M. Pap, and S. Mukhtar (1998). “Automatically finding solar active regions using SoHO/MDI photograms and magnetograms,” Proc. SoHO 6/GONG '98 Workshop on Structure and Dynamics of the Sun, pp. 979-984.

1997

M. Turmon (1997). “Identification of Solar Features via Markov Random Fields,” Proc. Second Conf. International Assoc. for Statistical Computing, pp. 194–200.

M. Turmon and J. Pap (1997). “Segmenting Chromospheric Images with Markov Random Fields,” Statistical Challenges in Modern Astronomy II, ed. G. Babu and E. Feigelson, pp. 408–411, Springer.

M. Turmon, S. Mukhtar, and J. Pap (1997). “Bayesian Inference for Identifying Solar Active Regions,” Proc. Third Conf. on Knowledge Discovery and Data Mining, ed. D. Heckerman, H. Mannila, D. Pregibon, and R. Uthurusamy, pp. 267-270, MIT Press. Download (CL 97-0755).

M. Turmon and S. Mukhtar (1997). “Recognizing Chromospheric Objects via Markov Chain Monte Carlo,” Proc. IEEE Intl. Conf. Image Processing, vol. III, pp. 320–323. Download (CL 97-1147).

J. Pap, M. Turmon, S. Mukhtar, R. Bogart , R. Ulrich, C. Frolich, and Ch. Wehrli (1997). “Automated Recognition and Characterization of Solar Active Regions based on the SOHO/MDI Images,” Proc. 31st ESLAB Symposium, pp. 477-482, Nordwijk, Netherlands.

1995

M. Turmon (1995). Assessing Generalization of Feedforward Neural Networks, PhD thesis, Cornell.

M. Turmon and T. L. Fine (1995). “Empirically Estimating Generalization Ability of Feedforward Neural Networks,” World Conference on Neural Networks, pp. 600-605. Invited paper.

M. Turmon and T. L. Fine (1995). “Sample Size Requirements for Feedforward Neural Networks,” Neural Information Processing Systems 7, ed. G. , pp. 327-334, Morgan-Kauffman.

M. Turmon and T. L. Fine (1995). “Assessing Generalization of Feedforward Neural Networks,” IEEE 1995 International Symposium on Information Theory, p. 168. Long paper.

1994

M. J. Turmon and M. I. Miller (1994). “Maximum-Likelihood estimation of constrained means and Toeplitz covariances with application to direction-finding,” IEEE Trans. on Signal Processing, 42(5), pp. 1074–1086.

1993

M. Turmon and T. L. Fine (1993). “Sample Size Requirements of Feedforward Neural Network Classifiers,” IEEE 1993 International Symposium on Information Theory, p. 432.

1990

M. J. Turmon (1990). “Maximum-likelihood estimation of constrained means and Toeplitz covariances with application to direction-finding,” M.S. thesis, Washington University, St. Louis.

1988

M. J. Turmon, M. I. Miller, D. L. Snyder, and J. A. O'Sullivan (1988). “Performance Evaluation of Maximum-Likelihood Toeplitz Covariance Estimates Generated Using the Expectation Maximization Algorithm,” Proc. Fourth ASSP Workshop on Spectrum Estimation and Modeling, pp. 182-185.

1987

M. J. Turmon and M. I. Miller (1987). “Simulation results for maximum-likelihood estimation of Toeplitz constrained covariances,” Proc. Twenty-first Annual Conference on Information Sciences and Systems.

1986

M. I. Miller, D. L. Snyder, and M. J. Turmon (1986). “Iterative maximum-likelihood estimation of Toeplitz-constrained covariances,” Proc. Twenty-fourth Annual Allerton Conference on Communication, Control and Computing, pp. 111-112.

M. I. Miller, D. L. Snyder, and M. J. Turmon (1986). “The application of maximum-entropy and maximum-likelihood for spectral estimation,” IEEE 1986 International Symposium on Information Theory.

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