Behavioral testing of cellular neural networks

J. Willis; J. Pineda de Gyvez

doi:10.1109/ISCAS.1994.409569

Behavioral testing of cellular neural networks

J. Willis, J. Pineda de Gyvez

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

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Abstract

This paper addresses the functional behavior of Cellular Neural Networks (CNN). The impact of variable convergence times on the proper operation of the network is discussed A test method is presented to determine the functionality of the network. The function fault models assume that the cells are unable to switch between limiting states. The proposed method attains 100% stuck-at fault coverage without any extra hardware for its implementation. Moreover, the required number of test vectors is constant and independent of the array size which makes it suitable for practical implementations. The paper discusses the new fault model, presents the algorithmic procedures and shows simulated testing results

Original language	English
Title of host publication	Proceedings of the 1994 IEEE International Symposium on Circuits and Systems, 1994, ISCAS '94, 30 May - 2 June 1994, London, United Kingdom
Place of Publication	New York
Publisher	Institute of Electrical and Electronics Engineers
Pages	229-232
Volume	6
ISBN (Print)	0-7803-1915-X
DOIs	https://doi.org/10.1109/ISCAS.1994.409569
Publication status	Published - 1994
Externally published	Yes

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10.1109/ISCAS.1994.409569

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@inproceedings{9a3ea831110847e8bee2a2c2caa774b1,

title = "Behavioral testing of cellular neural networks",

abstract = "This paper addresses the functional behavior of Cellular Neural Networks (CNN). The impact of variable convergence times on the proper operation of the network is discussed A test method is presented to determine the functionality of the network. The function fault models assume that the cells are unable to switch between limiting states. The proposed method attains 100% stuck-at fault coverage without any extra hardware for its implementation. Moreover, the required number of test vectors is constant and independent of the array size which makes it suitable for practical implementations. The paper discusses the new fault model, presents the algorithmic procedures and shows simulated testing results",

author = "J. Willis and {Pineda de Gyvez}, J.",

year = "1994",

doi = "10.1109/ISCAS.1994.409569",

language = "English",

isbn = "0-7803-1915-X",

volume = "6",

pages = "229--232",

booktitle = "Proceedings of the 1994 IEEE International Symposium on Circuits and Systems, 1994, ISCAS '94, 30 May - 2 June 1994, London, United Kingdom",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

}

Behavioral testing of cellular neural networks. / Willis, J.; Pineda de Gyvez, J.

Proceedings of the 1994 IEEE International Symposium on Circuits and Systems, 1994, ISCAS '94, 30 May - 2 June 1994, London, United Kingdom. Vol. 6 New York : Institute of Electrical and Electronics Engineers, 1994. p. 229-232.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Behavioral testing of cellular neural networks

AU - Willis, J.

AU - Pineda de Gyvez, J.

PY - 1994

Y1 - 1994

N2 - This paper addresses the functional behavior of Cellular Neural Networks (CNN). The impact of variable convergence times on the proper operation of the network is discussed A test method is presented to determine the functionality of the network. The function fault models assume that the cells are unable to switch between limiting states. The proposed method attains 100% stuck-at fault coverage without any extra hardware for its implementation. Moreover, the required number of test vectors is constant and independent of the array size which makes it suitable for practical implementations. The paper discusses the new fault model, presents the algorithmic procedures and shows simulated testing results

AB - This paper addresses the functional behavior of Cellular Neural Networks (CNN). The impact of variable convergence times on the proper operation of the network is discussed A test method is presented to determine the functionality of the network. The function fault models assume that the cells are unable to switch between limiting states. The proposed method attains 100% stuck-at fault coverage without any extra hardware for its implementation. Moreover, the required number of test vectors is constant and independent of the array size which makes it suitable for practical implementations. The paper discusses the new fault model, presents the algorithmic procedures and shows simulated testing results

U2 - 10.1109/ISCAS.1994.409569

DO - 10.1109/ISCAS.1994.409569

M3 - Conference contribution

SN - 0-7803-1915-X

VL - 6

SP - 229

EP - 232

BT - Proceedings of the 1994 IEEE International Symposium on Circuits and Systems, 1994, ISCAS '94, 30 May - 2 June 1994, London, United Kingdom

PB - Institute of Electrical and Electronics Engineers

CY - New York

ER -

Behavioral testing of cellular neural networks

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