| 1 |
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
DOI
|
| 2 |
M.Tatsuno, 'Computational Neuroscience-Methods in Neuronal modeling,' Educational Lecture, BSI Retreat, Oiso, Japan, Sept. 18-20, 2000
|
| 3 |
J. Albus, 'A theory of cerebellar function,' Mathematical Biosciences, vol. 10, pp. 25-61, 1971
DOI
ScienceOn
|
| 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
DOI
ScienceOn
|
| 5 |
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
DOI
ScienceOn
|
| 6 |
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
DOI
ScienceOn
|
| 7 |
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
DOI
ScienceOn
|
| 8 |
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
|
| 9 |
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
DOI
|
| 10 |
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
DOI
ScienceOn
|
| 11 |
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
|
| 12 |
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
DOI
ScienceOn
|
| 13 |
L. Holmstrom and P. Koistinen, 'Using additive noise in back-propagation training,' IEEE Trans. Neural Networks, vol. 3, pp. 24-38, 1992
DOI
ScienceOn
|
| 14 |
J. Karhunen, et al., 'A class of neural networks for independent component analysis,' IEEE Trans. Neural Networks, vol. 8, pp. 486-504, 1997
DOI
ScienceOn
|
| 15 |
S.-H. Oh, 'Improving the error back-propagation algorithm with a modified error function,' IEEE Trans. Neural Networks, vol. 8, pp. 799-803, 1997
DOI
ScienceOn
|
| 16 |
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
DOI
ScienceOn
|
| 17 |
K. Matsuoka, 'Noise injection into inputs in back-propagation learning,' IEEE Trans. Systems, Man, and Cybernetics, vol. 22, no. 3, pp. 436-440, 1992
DOI
ScienceOn
|
| 18 |
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
DOI
ScienceOn
|
| 19 |
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
DOI
|
| 20 |
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
|
| 21 |
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
|
| 22 |
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
DOI
ScienceOn
|
| 23 |
A. Hyvarinen, P. O. Hoyer, and M. Inki, 'Topographic independent component analysis,' Neural Cmputation, vol.13, no.7, pp.1527-1558, 2001
DOI
ScienceOn
|
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