Using multithreshold quadratic sigmoidal neurons to improve classification capability of multilayer perceptrons

Cheng Chin Chiang, Hsin-Chia Fu

Research output: Contribution to journalArticlepeer-review

Abstract

This letter proposes a new type of neurons called multithreshold quadratic sigmoidal neurons to improve the classification capability of multilayer neural networks. In cooperation with single-threshold quadratic sigmoidal neurons, the multithreshold quadratic sigmoidal neurons can be used to improve the classification capability of multilayer neural networks by a factor of four compared to committee machines and by a factor of two compared to the conventional sigmoidal multilayer perceptrons.
Original languageEnglish
Pages (from-to)516 - 519
Number of pages4
JournalIEEE Transactions on Neural Networks
Volume5
Issue number3
DOIs
StatePublished - May 1994

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