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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

A pattern recognition approach to transistor array parameter variance

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Autor(es):
Costa, Luciano da F. [1] ; Silva, Filipi N. [1] ; Comin, Cesar H. [2]
Número total de Autores: 3
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Sao Carlos Inst Phys, Sao Carlos, SP - Brazil
[2] Univ Fed Sao Carlos, Dept Comp Sci, Sao Carlos, SP - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS; v. 499, p. 176-185, JUN 1 2018.
Citações Web of Science: 0
Resumo

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)

Processo FAPESP: 15/18942-8 - Associando redes complexas com espaços efetivos de atributos
Beneficiário:Cesar Henrique Comin
Linha de fomento: Bolsas no Brasil - Pós-Doutorado
Processo FAPESP: 15/22308-2 - Representações intermediárias em Ciência Computacional para descoberta de conhecimento
Beneficiário:Roberto Marcondes Cesar Junior
Linha de fomento: Auxílio à Pesquisa - Temático
Processo FAPESP: 15/08003-4 - Abordagem de redes complexas em e-Science e dados dinâmicos
Beneficiário:Filipi Nascimento Silva
Linha de fomento: Bolsas no Brasil - Pós-Doutorado
Processo FAPESP: 11/50761-2 - Modelos e métodos de e-Science para ciências da vida e agrárias
Beneficiário:Roberto Marcondes Cesar Junior
Linha de fomento: Auxílio à Pesquisa - Temático