Convergence of a hebbian-type learning algorithm

Qingfu Zhang*, Yiu-Wing Leung

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

6 Citations (Scopus)


A Hebbian-type learning algorithm was proposed in [1] for extracting the minor components of the input signals. In this paper, we demonstrate that some solutions of the averaging differential equation of this algorithm can become unbounded in a finite time. We derive five sufficient conditions to ensure that the solutions of its averaging differential equation are bounded and can be extended to the time interval [0, ∞). Any one of these conditions can guarantee that this algorithm can be used to lind the minor components of the input signals.

Original languageEnglish
Pages (from-to)1599-1601
Number of pages3
JournalIEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing
Issue number12
Publication statusPublished - Dec 1998

Scopus Subject Areas

  • Signal Processing
  • Electrical and Electronic Engineering


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