Fast learning algorithm to improve performance of Quickprop

Chi Chung Cheung, Sin Chun Ng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)


Quickprop is one of the most popular fast learning algorithms in training feed-forward neural networks. Its learning rate is fast; however, it is still limited by the gradient of the backpropagation algorithm and it is easily trapped into a local minimum. Proposed is a new fast learning algorithm to overcome these two drawbacks. The performance investigation in different learning problems (applications) shows that the new algorithm always converges with a faster learning rate compared with Quickprop and other fast learning algorithms. The improvement in global convergence capability is especially large, which increased from 4 to 100 in one learning problem.

Original languageEnglish
Pages (from-to)678-679
Number of pages2
JournalElectronics Letters
Issue number12
Publication statusPublished - 7 Jun 2012

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


Dive into the research topics of 'Fast learning algorithm to improve performance of Quickprop'. Together they form a unique fingerprint.

Cite this