Multiple hard fault classification in analog circuits using learning vector quantization neural networks

Joint Authors

al-Jamal, M. A.
Abu al-Yazid, M. F.

Source

Al-Manarah

Issue

Vol. 4, Issue 2 (31 Jul. 1999), pp.137-153, 17 p.

Publisher

Al al-Bayt University Deanship of Academic Research and Graduate Studies

Publication Date

1999-07-31

Country of Publication

Jordan

No. of Pages

17

Main Subjects

Information Technology and Computer Science

Topics

Abstract EN

A new neural network-based fault classification strategy for hard multiple faults in analog circuits is proposed The magnitude of the' harmonics of the Fourier components of the circuit response at different lest nodes due to a sinusoidal input signal are first measured or simulated A selection criterion for determining the best components that describe the circuit behavior under fault-free (nominal) and fault situations is presented An algorithm that estimates the overlap between different faults in the measurement space is also introduced I he learning vector quantization neural network is then effectively named to classify circuit faults Performance measures reveal very high classification accuracy in both naming and testing stages A detailed example which demonstrates the proposed strategy, is described.

American Psychological Association (APA)

al-Jamal, M. A.& Abu al-Yazid, M. F.. 1999. Multiple hard fault classification in analog circuits using learning vector quantization neural networks. Al-Manarah،Vol. 4, no. 2, pp.137-153.
https://search.emarefa.net/detail/BIM-169140

Modern Language Association (MLA)

al-Jamal, M. A.& Abu al-Yazid, M. F.. Multiple hard fault classification in analog circuits using learning vector quantization neural networks. Al-Manarah Vol. 4, no. 2 (Jul. 1999), pp.137-153.
https://search.emarefa.net/detail/BIM-169140

American Medical Association (AMA)

al-Jamal, M. A.& Abu al-Yazid, M. F.. Multiple hard fault classification in analog circuits using learning vector quantization neural networks. Al-Manarah. 1999. Vol. 4, no. 2, pp.137-153.
https://search.emarefa.net/detail/BIM-169140

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 152-153

Record ID

BIM-169140