@article{60a000cd460e4562a6b60fe4398d0bca,
title = "A self-stabilized minor subspace rule",
abstract = "In this letter, we present a minor subspace rule that extracts the subspace that spans the m minor components of a n-dimensional vector stationary random process, m < n. The algorithm is self-stabilizing such that the subspace vectors do not need to be periodically normalized to unit modulus, and the algorithm does not require matrix inversions or divides to maintain its stable behavior.",
keywords = "Adaptive algorithm, Minor component analysis, Subspace methods",
author = "Douglas, {Scott C.} and Kung, {S. Y.} and Amari, {Shun Ichi}",
note = "Funding Information: Manuscript received June 17, 1998. This work was supported in part by the office of Research and Development under Contract 98F135700-000. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. G. Ramponi. S. C. Douglas is with the Department of Electrical Engineering, Southern Methodist University, Dallas, TX 75275 USA (e-mail: douglas@seas.smu.edu). S.-Y. Kung is with the Department of Electrical Engineering, Princeton University, Princeton, NJ 08544 USA. S. Amari is with the Brain-Style Information Systems Group, RIKEN Brain Science Institute, Saitama 351-0198, Japan. Publisher Item Identifier S 1070-9908(98)09410-3.",
year = "1998",
doi = "10.1109/97.735427",
language = "English (US)",
volume = "5",
pages = "328--330",
journal = "IEEE Signal Processing Letters",
issn = "1070-9908",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "12",
}