References
Abdi, H. and Willians, L. J., 2010- Principal Component Analysis. WIREs Comp Stat 2, 433–459.
Amaziane, B., Bourgeat, A., Jurak, M., 2006- Effective macrodifusion in solute transport through heterogeneous porous media. Multiscale Modeling and Simulation 5, 184–204.
Avseth, P., Mukerji, T. and Mavko, G., 2005- Quantitative Seismic Interpretation. Applying Rock Physics to Reduce Interpretation Risk. Cambridge University Press, Cambridge, New York, Melbourne.
Battiato, S., Mancuso, M., Bosco, A. and Guarnera, M., 2001- Psychovisual and statistical optimization of quantization tables for DCT compression engines. In: Proceed- ings of the 11th International Conference on Image Analysis and Processing, ICIAP'01, Palermo, Italy, p. 602.
Bhatia, N. and Vandana, A., 2010- Survey of nearest neighbor techniques. International Journal of Computer Science and Information Security 2 (8), 302–305.
Blinn, J. F., 1993- What's the deal with the DCT. IEEE Computer Graphics and Applications 13 (4), 78–83.
Burden, R. L., Faires, J. D., 1985- Numerical Analysis, Third Edition Prindle, Weber and Schimidt, Boston.
Carrasquilla, A. and Leite, M. V., 2009- Fuzzy logic in the simulation of sonic log using as input combinations of gamma ray, resistivity, porosity and density well logs from Namorado Oilfield. In: Proceedings of the 11th International Congress of the Brazilian Geophysical Society, Salvador, Brazil.
Coconi-Morales, E., Ronquillo-Jarillo, G. and Campos-Enríquez, J. O., 2010- Multi-scale analysis of well-logging data in petrophysical and stratigraphic correlation. Geofísica Internacional 49 (2), 55–67.
Comon, P., 1994- Independent component analysis: a new concept?. Signal Proces- sing, 36; 287–314.
Cover, T. M. and Hart, P. E., 1967- Nearest neighbor pattern classification. IEEE Transac- tions on Information Theory 13 (1), 21–27.
Doyen, P. M., 2007- Seismic reservoir characterization: an earth modelling perspec- tive. EAGE Publications, Houten, The Netherlands.
Dubrule, O., 1994- Estimating or choosing a geostatistical model. In: Dimitrako- poulos, R. (Ed.), Geostatistics for the Next Century. Kluwer Academic Publishers, Dordcrecht, The Netherlands, pp. 3–14.
Duda, R. and Hart, P., 1973- Pattern Classification and Scene Analysis. Wiley, New-York.
Farina, A. and Studer, F. A., 1984- Application of Gram-Schmidt algorithm optimum radar signal processing. IEEE Proceedings Part F 131, 139–145.
Franklin, J. N., 1968- Matrix Theory. Englewood Cliffs: Prentice-Hall. 292 pp.
Grana, D., Pirrone, M. and Mukerji, T., 2012- Quantitative log interpretation and uncertainty propagation of petrophysical properties and facies classification from rock-physics modeling and formation evaluation analysis. Geophysics 77, WA45–WA63.
Hyvärinen, A., 1999- Fast and robust fixed-point algorithms for independent component analysis. IEEE Transactions on Neural Networks 10 (3), 626–634.
Hyvärinen, A., Karhunen, J. and Oja, E., 2001- Independent Component Analysis. John Wiley and Sons, Toronto 481 pp.
Liu, Y., Weisberg, R. H., Mooers, C. N. K., 2006- Performance evaluation of the self- organizing map for feature extraction. Journal of Geophysical Research 111, C05018, http://dx.doi.org/10.1029/2005JC003117.
MacQueen, J. B., 1967- Some methods for classification and analysis of multivariate observations. In: Le Cam, L.M., Neyman, J. (Eds.), Proceedings of the fifth Berkeley Symposium on Mathematical Statistics and Probability, University of California Press, pp. 281–297.
Martucci, S. A., 1994- Symmetric convolution and the discrete sine and cosine transforms. IEEE Transactions on Signal Processing SP-42, 1038–1051.
Messina, A. and Langer, H., 2011- Pattern recognition of volcanic tremor data on Mt. Etna (Italy) with KKAnalysis—a software program for unsupervised classifica- tion. Computers and Geosciences 37, 953–961.
Mitchell, T., 1997- Machine Learning. McGraw-Hill Higher Education, New York 432 pp.
Oppenheim, A. V., Schafer, R. W. and Buck, J. R., 2009- Discrete-Time Signal Processing, 3th ed. Prentice Hall, NJ 1120 pp.
Rao, K. R. and Yip, P., 1990- Discrete Cosine Transform: Algorithms, Advantages, Applications. Academic Press, Boston 512 pp.
Rosati, I. and Cardarelli, E., 1997- Statistical pattern recognition technique to enhance anomalies in magnetic surveys. Journal of Applied Geophysics 37 (2), 55–66.
Russell, S. and Norvig, P., 2002- Artificial Intelligence: A Modern Approach. Prentice Hall, Essex, England 478 pp.
Rutherford, S. R. and Willians, R. H., 1989- Amplitude versus offset variations in gas sands. Geophysics 54 (06), 680–688.
Sanchetta, A. C., Leite, E. P. and Honório, B. C. Z., 2013- Facies recognition using a smoothing process through Fast Independent Component Analysis and Discrete Cosine Transform. Computers and Geosciences 57, 175-182.
Schuerman, J., 1996- Pattern Classification: A Unified View of Statistical and Neural Approaches. Wiley and Sons, New York 392 pp.
Simonoff, J. S., 1996- Smoothing Methods in Statistics. Springer, New York 368 pp.
Toussaint, G. T., 2005- Geometric proximity graphs for improving nearest neighbor methods in instance-based learning and data mining. International Journal of Computational Geometry and Applications 15 (2), 101–150.
Turlapaty, A. C., Anantharaj, V. G. and Younan, N. H., 2010- A pattern recognition based approach to consistency analysis of Geophysical datasets. Computers and Geosciences 36, 464–476.