Discrete wavelet transform and radial basis neural network for semiconductor wet-etching fabrication flow-rate analysis

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This paper presents research that uses discrete wavelet transform (DWT) and radial basis neural network for automatic classification. The flow rate of a wet-etching fabrication facility for a single wafer can be analyzed automatically. The electrical signal of a flow meter is collected and decomposed by means of DWT. The signal power of the coefficients processed by the DWT is fed into the radial basis neural network for initial classification. A digital filter for post signal processing and a user-defined threshold value are applied; calculations for successful identification rate take place at the final step. The research results are applicable to automatic identification functions for in situ fabrication monitoring.

Original languageEnglish
Article number6125246
Pages (from-to)865-875
Number of pages11
JournalIEEE Transactions on Instrumentation and Measurement
Issue number4
Publication statusPublished - 2012 Apr 1


All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Electrical and Electronic Engineering

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