Combining DEKF algorithm and trace rule for fast on-line invariance extraction and recognition

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

2 Scopus Citations
View graph of relations

Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Pages (from-to)493-501
Journal / PublicationPattern Recognition Letters
Volume21
Issue number6-7
Publication statusPublished - Jun 2000

Abstract

A self-organizing network is used to perform invariance extraction and recognition of handwritten digits. To extract the invariance effectively, we propose to combine the trace learning rule and the on-line dual extended Kalman filter (DEKF) algorithm. Furthermore, a new activation function is suggested to replace the traditional sigmoid activation function so as to reduce the sensitivity of the extracted features to samples with large variance. Computer simulations show that both the learning speed and the recognition rate are improved using a compact network. © 2000 Elsevier Science B.V.

Research Area(s)

  • EKF Algorithm, Neural networks, Pattern recognition, Pruning, Trace Rule