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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A pattern recognition approach to transistor array parameter variance

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Author(s):
Costa, Luciano da F. [1] ; Silva, Filipi N. [1] ; Comin, Cesar H. [2]
Total Authors: 3
Affiliation:
[1] Univ Sao Paulo, Sao Carlos Inst Phys, Sao Carlos, SP - Brazil
[2] Univ Fed Sao Carlos, Dept Comp Sci, Sao Carlos, SP - Brazil
Total Affiliations: 2
Document type: Journal article
Source: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS; v. 499, p. 176-185, JUN 1 2018.
Web of Science Citations: 0
Abstract

The properties of semiconductor devices, including bipolar junction transistors (BJTs), are known to vary substantially in terms of their parameters. In this work, an experimental approach, including pattern recognition concepts and methods such as principal component analysis (PCA) and linear discriminant analysis (LDA), was used to experimentally investigate the variation among BJTs belonging to integrated circuits known as transistor arrays. It was shown that a good deal of the devices variance can be captured using only two PCA axes. It was also verified that, though substantially small variation of parameters is observed for BJT from the same array, larger variation arises between BJTs from distinct arrays, suggesting the consideration of device characteristics in more critical analog designs. As a consequence of its supervised nature, LDA was able to provide a substantial separation of the BJT into clusters, corresponding to each transistor array. In addition, the LDA mapping into two dimensions revealed a clear relationship between the considered measurements. Interestingly, a specific mapping suggested by the PCA, involving the total harmonic distortion variation expressed in terms of the average voltage gain, yielded an even better separation between the transistor array clusters. All in all, this work yielded interesting results from both semiconductor engineering and pattern recognition perspectives. (c) 2018 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 15/18942-8 - Associating complex networks with effective feature spaces
Grantee:Cesar Henrique Comin
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 15/22308-2 - Intermediate representations in Computational Science for knowledge discovery
Grantee:Roberto Marcondes Cesar Junior
Support type: Research Projects - Thematic Grants
FAPESP's process: 15/08003-4 - Complex network approach to e-Science and dynamic datasets
Grantee:Filipi Nascimento Silva
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 11/50761-2 - Models and methods of e-Science for life and agricultural sciences
Grantee:Roberto Marcondes Cesar Junior
Support type: Research Projects - Thematic Grants