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

研究成果: Article

2 引文 斯高帕斯(Scopus)

摘要

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.

原文English
文章編號6125246
頁(從 - 到)865-875
頁數11
期刊IEEE Transactions on Instrumentation and Measurement
61
發行號4
DOIs
出版狀態Published - 2012 四月 1

    指紋

All Science Journal Classification (ASJC) codes

  • Instrumentation
  • Electrical and Electronic Engineering

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