DSP-based fuzzy neural network and its application in speech recognition

Shin Chyan Chen*, Chen Chien Hsu, Wei Yen Wang

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)


A fuzzy-neural network needs to be trained through a learning process, so that suitable membership functions and weightings can be obtained. However, most neural networks are only simulated by computer software, which are not practical for real applications. It is therefore our objective to design an integrated circuit system based on a DSP processor with powerful arithmetical capabilities and fast data processing, and relevant peripheral devices to implement the fuzzy-neural network. In terms of implementation cost and feasibility for practical applications, this DSP-based fuzzy-neural network will be more practical and usable. Finally, a prospective application of the DSP-processor-based fuzzy neural network to recognize speech from a non-designated person is proposed.

Original languageEnglish
Pages (from-to)VI-110 - VI-113
JournalProceedings of the IEEE International Conference on Systems, Man and Cybernetics
Publication statusPublished - 1999
Externally publishedYes
Event1999 IEEE International Conference on Systems, Man, and Cybernetics 'Human Communication and Cybernetics' - Tokyo, Jpn
Duration: 1999 Oct 121999 Oct 15

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture


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