Kernel wiener filter using canonical correlation analysis framework

IEEE Workshop on Statistical Signal Processing Proceedings

Volumn 2005, Issue , 2005, Pages 769-774

  Yamada, Makoto ^a   Azimi Sadjadi, Mahmood R ^a  

^a Department of Chemical and Biological Engineering and School of Biomedical Engineering   (United States)

Author keywords

CCA; Kernel Wiener filter; Mean shift procedure; Pre image

Indexed keywords

DATABASE SYSTEMS; OPTIMIZATION; PROBLEM SOLVING; SIGNAL ANALYSIS;

CANONICAL CORRELATION ANALYSIS (CCA); KERNEL GRAM MATRICES; KERNEL WIENER FILTERS; MEAN SHIFT PROCEDURE;

SIGNAL FILTERING AND PREDICTION;

EID: 33947179966     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ssp.2005.1628697     Document Type: Conference Paper

References (15)

1. H. Hotelling, "Relation between two sets of variates," Biometrika, vol. 28 pp. 321-377, 1936
2. T. W. Anderson, An Introduction to multivariate statistical analysis, New York: Wiley, 2003.
3. L. L. Scharf, Statistical Signal Processing. MA:Addison-Wesley, 1991, pp. 330-331.
4. A. Pezeshki, "Two-channel signal processing in canonical coordinates," Ph.D. Dissertation, Colorado State University, Fort Collins, CO, Oct. 2004.
5. B. Schölkopf and A. J. Smola, Learning with Kernels, Support Vector Machines, Regularization, Optimization, and Beyond. Cambridge, MA: MIT Press, 2002
6. A. Pezeshki, L. L. Scharf, M. R. Azimi-Sadjadi, "Empirical canonical coordinate decompositions in subspaces for two-channel linear and nonlinear maps," IEEE Trans, on Signal Processing submitted sept.2004, under revision.
7. A. Pezeshki, M. R. Azimi-Sadjadi, and L. L. Scharf, "Kernel-based canonical coordinate decomposition of two-channel nonlinear maps," Proc. 2004 Int. Joint Conf. Neural Networks (IJCNN2004), pp. 3019-3024, July 2004.
8. L. L. Scharf and C. T. Mullis, "Canonical coordinates and the geometry of inference, rate and capacity," IEEE Trans. on Signal Processing, vol. 48, pp. 824-831, March 2000.
9. Y. Washizawa and Y. Yamashita, "Kernel Wiener Filter", Workshop on Information-Based Induction Sciences (IBIS), Nov 11-12. 2003 (Japanese).
10. S. Mika, B. Schölkopf, A. Smola, K.R.Müller, M. Scholz, and G. Rätsch, J. Weston, "Kernel PCA and denoising in feature spaces," Advances in Neural Information Processing Systems 11, pages 536 - 542, Cambridge, MA, 1999. MIT Press.
11. G. Bakir, J. Weston, and B. Schölkopf, "Learning to Find Pre-Images," Advances in Neural Information Processing Systems 16, Cambridge, MA, 2004. MIT Press.
12. M. Fashing and C. Tomasi, "Mean shift is a Bound Optimization", IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 27, No.3, March 2005
13. V. N. Vapnik, The Nature of Statistical Learning Theory. Springer, 1995
14. K. Müller, S. Mika, G.Rätsch, K. Tsuda, and B. Schölkopf, "An Introduction to Kernel-Based Learing Algorithms," IEEE Trans. on Neural Networks, Vol.12,No.2,pp.181-201, 2001
15. R. O. Duda, P. E. Hart, and D. G. Stork, Pattern Classification (2nd ed), New York: Wiley, 2001.