On gradient adaptation with unit-norm constraints

Scott C. Douglas, Shun Ichi Amari, S. Y. Kung

Research output: Contribution to journalArticlepeer-review

51 Scopus citations


In this correspondence, we describe gradient-based adaptive algorithms within parameter spaces that are specified by ∥w∥ = 1, where ∥·∥ is any vector norm. We provide several algorithm forms and relate them to true gradient procedures via their geometric structures. We also give algorithms that mitigate an inherent numerical instability for L2-norm-constrained optimization tasks. Simulations showing the performance of the techniques for independent component analysis are provided.

Original languageEnglish (US)
Pages (from-to)1843-1847
Number of pages5
JournalIEEE Transactions on Signal Processing
Issue number6
StatePublished - 2000
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering


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