참고문헌
- M.Tatsuno, 'Computational Neuroscience-Methods in Neuronal modeling,' Educational Lecture, BSI Retreat, Oiso, Japan, Sept. 18-20, 2000
- J. Albus, 'A theory of cerebellar function,' Mathematical Biosciences, vol. 10, pp. 25-61, 1971 https://doi.org/10.1016/0025-5564(71)90051-4
- A. J. Bell and T. J. Sejnowski, 'The independent components of natural scenes are edge filters,' Vision Research, vol. 37, pp. 3327-3338, 1997 https://doi.org/10.1016/S0042-6989(97)00121-1
- A. Hyvarinen, P. O. Hoyer, and M. Inki, 'Topographic independent component analysis,' Neural Cmputation, vol.13, no.7, pp.1527-1558, 2001 https://doi.org/10.1162/089976601750264992
- A. Hyvarinen, P. O. Hoyer, and J. Hurri, 'Extensions of ICA as models of natural images and visual processing,' Proceedings of ICA, April 1-4, 2003, Nara, Japan
- J. H. Lee and S.-Y. Lee, 'On the efficient speech feature extraction based on independent component analysis,' Neural Processing Letters, vol. 15, no. 3, pp. 235-245, June 2002 https://doi.org/10.1023/A:1015777200976
- U.-M. Bae and S.-Y. Lee, 'A complementary approach to blind signal separation for rea-world speech recognition,' Advances in Neural Information Processing Systems 13, pp, 765-771, Nov. 2000
- I. V. Tetko and A. E. P. Villa, 'Efficient partition of learning data sets for neural network training,' Neural Networks, vol. 10, pp. 1361-1374, 1997 https://doi.org/10.1016/S0893-6080(97)00005-1
- C. Wang and J. C. Principe, 'Training neural networks with additive noise in the desired signal,' IEEE Trans. Neural Networks, vol. 10, pp. 1511-1517, 1999 https://doi.org/10.1109/72.809097
- L. Holmstrom and P. Koistinen, 'Using additive noise in back-propagation training,' IEEE Trans. Neural Networks, vol. 3, pp. 24-38, 1992 https://doi.org/10.1109/72.105415
- K. Matsuoka, 'Noise injection into inputs in back-propagation learning,' IEEE Trans. Systems, Man, and Cybernetics, vol. 22, no. 3, pp. 436-440, 1992 https://doi.org/10.1109/21.155944
- S.-Y. Yoon and S.-Y. Lee, 'Training algorithm with incomplete data for feed-forward neural networks,' Neural Processing Letters, vol. 10, pp. 171-179, 1999 https://doi.org/10.1023/A:1018772122605
- Z. Ghahramani and M. Jordan, 'Supervised learning from incomplete data via an EM approach,' Advances in Neural Information Processing Systems 6, pp. 120-127, Nov. 1994
- B. Kamgar-Parsi, B. Kamgar-Parsi, J. E. Dayhoff, and A. K. Jain, 'Improving classification boundaries by exemplar generation for visual pattern discrimination,' Proc. IJCNN2001, vol. 4, pp. 2969-2974 https://doi.org/10.1109/IJCNN.2001.938850
- B. A. Olshausen and D. J. Field, 'Emergence of simple-cell receptive field properties by learning a sparse code for natural images,' Nature, vol. 381, pp. 607-609, 13 June, 1996 https://doi.org/10.1038/381607a0
- T.-W. Lee, et al., 'A unifying information-theoretic framework for independent component analysis,' Computers & Mathematics with Applications, vol. 31, no. 11, pp. 1-21, March 2000 https://doi.org/10.1016/S0898-1221(00)00101-2
- S.-H. Oh, A. Cichocki, S. Choi, S.-I. Amari, and S.-Y. Lee., 'Comparison of ICA/BSS algorithms in noisy environment,' Proc. ICONIP, vol. 2, pp. 1192-1197, Nov. 2000
- M. Girolami, A. Cichocki, and S.-I. Amari, 'A common neural-network model for unsupervised exploratory data analysis and independent component analysis,' IEEE Trans. Neural Networks, vol. 9, no. 6, Nov. 1998 https://doi.org/10.1109/72.728398
- J. Karhunen, et al., 'A class of neural networks for independent component analysis,' IEEE Trans. Neural Networks, vol. 8, pp. 486-504, 1997 https://doi.org/10.1109/72.572090
- S.-H. Oh, 'Improving the error back-propagation algorithm with a modified error function,' IEEE Trans. Neural Networks, vol. 8, pp. 799-803, 1997 https://doi.org/10.1109/72.572117
- J. C. Principe, et al., 'Learning from examples with information theoretic criteria,' The Journal of VLSI Signal Proc., special issue on neural networks, vol. 26, pp. 61-77, Aug. 2000 https://doi.org/10.1023/A:1008143417156
- R. Kamimura and S. Nakanishi, 'Hidden information maximization for feature detection and rule discovery,' Network: Computation in Neural Systems, vol. 6, pp. 577-602, 1995 https://doi.org/10.1088/0954-898X/6/4/004
- J. J. Hull, 'A database for handwritten text recognition research,' IEEE Trans. Pat. Ana. Mach. Int., vol. 15, no. 5, pp. 550-554, May 1994 https://doi.org/10.1109/34.291440