Title :
Principal curves with bounded turn
Author :
Sandilya, S. ; Kulkarni, S.R.
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ, USA
Abstract :
Principal curves, like principal components, are a tool used in multivariate analysis for ends like feature extraction. Defined in their original form, principal curves need not exist for general distributions. The existence of principal curves with bounded length and a learning algorithm for such curves for any distribution that satisfies some minimal regularity conditions has been shown. We define principal curves with bounded turn, show that they exist, and present a learning algorithm for them
Keywords :
feature extraction; information theory; statistical analysis; bounded turn; distribution; feature extraction; learning algorithm; multivariate analysis; principal curves; regularity conditions; Feature extraction;
Conference_Titel :
Information Theory, 2000. Proceedings. IEEE International Symposium on
Conference_Location :
Sorrento
Print_ISBN :
0-7803-5857-0
DOI :
10.1109/ISIT.2000.866619
