IEICE TRANSACTIONS on Fundamentals
Parallel Architecture for Generalized LFSR in LSI Built-In Self Testing
Summary :
This paper presents a new architecture for multiple-input signature analyzers. The proposed signature analyzer with Hδ inputs is designed by parallelizing a GLFSR(δ,m), where δ is the number of input signals and m is the number of stages in the feedback shift register. The GLFSR, developed by Pradhan and Gupta, is a general framework for representing LFSR-based signature analyzers. The parallelization technique described in this paper can be applied to any kind of GLFSR signature analyzer, e. g. , SISRs, MISRs, multiple MISRs and MLFSRs. It is shown that a proposed signature analyzer with Hδ inputs requires less complex hardware than either single GLFSR(Hδ,m)s or a parallel construction of the H original GLFSR(δ,m)s. It is also shown that the proposed signature analyzer, while requiring simpler hardware, has comparable aliasing probability with analyzers using conventional GLFSRs for some CUT error models of the same test response length and test time. The proposed technique would be practical for testing CUTs with a large number of output sequences, since the test circuit occupies a smaller area on the LSI chip than the conventional multiple-input signature analyzers of comparable aliasing probability.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E81-A No.6 pp.1252-1261
- Publication Date
- 1998/06/25
- Publicized
- Online ISSN
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- Type of Manuscript
- Category
- Reliability and Fault Analysis
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Tomoko K. MATSUSHIMA, Toshiyasu MATSUSHIMA, Shigeichi HIRASAWA, "Parallel Architecture for Generalized LFSR in LSI Built-In Self Testing" in IEICE TRANSACTIONS on Fundamentals,
vol. E81-A, no. 6, pp. 1252-1261, June 1998, doi: .
Abstract: This paper presents a new architecture for multiple-input signature analyzers. The proposed signature analyzer with Hδ inputs is designed by parallelizing a GLFSR(δ,m), where δ is the number of input signals and m is the number of stages in the feedback shift register. The GLFSR, developed by Pradhan and Gupta, is a general framework for representing LFSR-based signature analyzers. The parallelization technique described in this paper can be applied to any kind of GLFSR signature analyzer, e. g. , SISRs, MISRs, multiple MISRs and MLFSRs. It is shown that a proposed signature analyzer with Hδ inputs requires less complex hardware than either single GLFSR(Hδ,m)s or a parallel construction of the H original GLFSR(δ,m)s. It is also shown that the proposed signature analyzer, while requiring simpler hardware, has comparable aliasing probability with analyzers using conventional GLFSRs for some CUT error models of the same test response length and test time. The proposed technique would be practical for testing CUTs with a large number of output sequences, since the test circuit occupies a smaller area on the LSI chip than the conventional multiple-input signature analyzers of comparable aliasing probability.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e81-a_6_1252/_p
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@ARTICLE{e81-a_6_1252,
author={Tomoko K. MATSUSHIMA, Toshiyasu MATSUSHIMA, Shigeichi HIRASAWA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Parallel Architecture for Generalized LFSR in LSI Built-In Self Testing},
year={1998},
volume={E81-A},
number={6},
pages={1252-1261},
abstract={This paper presents a new architecture for multiple-input signature analyzers. The proposed signature analyzer with Hδ inputs is designed by parallelizing a GLFSR(δ,m), where δ is the number of input signals and m is the number of stages in the feedback shift register. The GLFSR, developed by Pradhan and Gupta, is a general framework for representing LFSR-based signature analyzers. The parallelization technique described in this paper can be applied to any kind of GLFSR signature analyzer, e. g. , SISRs, MISRs, multiple MISRs and MLFSRs. It is shown that a proposed signature analyzer with Hδ inputs requires less complex hardware than either single GLFSR(Hδ,m)s or a parallel construction of the H original GLFSR(δ,m)s. It is also shown that the proposed signature analyzer, while requiring simpler hardware, has comparable aliasing probability with analyzers using conventional GLFSRs for some CUT error models of the same test response length and test time. The proposed technique would be practical for testing CUTs with a large number of output sequences, since the test circuit occupies a smaller area on the LSI chip than the conventional multiple-input signature analyzers of comparable aliasing probability.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - Parallel Architecture for Generalized LFSR in LSI Built-In Self Testing
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1252
EP - 1261
AU - Tomoko K. MATSUSHIMA
AU - Toshiyasu MATSUSHIMA
AU - Shigeichi HIRASAWA
PY - 1998
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E81-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1998
AB - This paper presents a new architecture for multiple-input signature analyzers. The proposed signature analyzer with Hδ inputs is designed by parallelizing a GLFSR(δ,m), where δ is the number of input signals and m is the number of stages in the feedback shift register. The GLFSR, developed by Pradhan and Gupta, is a general framework for representing LFSR-based signature analyzers. The parallelization technique described in this paper can be applied to any kind of GLFSR signature analyzer, e. g. , SISRs, MISRs, multiple MISRs and MLFSRs. It is shown that a proposed signature analyzer with Hδ inputs requires less complex hardware than either single GLFSR(Hδ,m)s or a parallel construction of the H original GLFSR(δ,m)s. It is also shown that the proposed signature analyzer, while requiring simpler hardware, has comparable aliasing probability with analyzers using conventional GLFSRs for some CUT error models of the same test response length and test time. The proposed technique would be practical for testing CUTs with a large number of output sequences, since the test circuit occupies a smaller area on the LSI chip than the conventional multiple-input signature analyzers of comparable aliasing probability.
ER -
English
