Convergence monitoring in generalized Hebbian learning

Andrew P. Paplinski

    Research output: Contribution to conferencePaper

    1 Citation (Scopus)

    Abstract

    In this paper we discuss monitoring of the convergence of the Generalized Hebbian Learning algorithm which performs Principal Component Analysis, or the Karhunen-Loeve transform. We start with presentation of the details of the internal structure of the algorithm. Next we consider a number of inter-related convergence conditions. Finally, we present example of image coding algorithm in which those conditions are verified.

    Original languageEnglish
    Pages1372-1376
    Number of pages5
    Publication statusPublished - 1 Jan 1998
    EventProceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3) - Anchorage, AK, USA
    Duration: 4 May 19989 May 1998

    Conference

    ConferenceProceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3)
    CityAnchorage, AK, USA
    Period4/05/989/05/98

    Cite this

    Paplinski, A. P. (1998). Convergence monitoring in generalized Hebbian learning. 1372-1376. Paper presented at Proceedings of the 1998 IEEE International Joint Conference on Neural Networks. Part 1 (of 3), Anchorage, AK, USA, .