PCA-based parametric fault analysis for analog integrated circuits

Author

Deng, Yong ; Shi, Yibing ; Zhou, Longfu

Author_Institution

Sch. of Autom. Eng., Univ. of Electron. Sci. & Technol., Chengdu, China

fYear

2009

fDate

23-25 July 2009

Firstpage

554

Lastpage

557

Abstract

The wavelet filtering technology and principal components analysis (PCA) is used to extract the signatures of circuits in this paper. Firstly, the output signal of the analog circuits is filtered by Harr wavelet packet. Then, the energetic values in eight subbands are extracted as the principal components. By comparison with the eigenvalues of the energetic relative matrices, different states of the circuits are identified. The idea is discussed and the result is given in the paper.

Keywords

Haar transforms; analogue integrated circuits; eigenvalues and eigenfunctions; matrix algebra; principal component analysis; wavelet transforms; Harr wavelet packet; analog integrated circuits; eigenvalues; energetic relative matrices; parametric fault analysis; principal components analysis; wavelet filtering technology; Analog circuits; Analog integrated circuits; Circuit faults; Circuit testing; Eigenvalues and eigenfunctions; Fault diagnosis; Filtering; Integrated circuit technology; Principal component analysis; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications, Circuits and Systems, 2009. ICCCAS 2009. International Conference on

Conference_Location

Milpitas, CA

Print_ISBN

978-1-4244-4886-9

Electronic_ISBN

978-1-4244-4888-3

Type

conf

DOI

10.1109/ICCCAS.2009.5250441

Filename

5250441