Error Moderation in Low-Cost Machine-Learning-Based Analog/RF Testing

Machine-learning-based test methods for analog/RF devices have been the subject of intense investigation over the last decade. However, despite the significant cost benefits that these methods promise, they have seen a limited success in replacing the traditional specification testing, mainly due to...

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Veröffentlicht in:	IEEE transactions on computer-aided design of integrated circuits and systems Jg. 27; H. 2; S. 339 - 351
Hauptverfasser:	Stratigopoulos, H.-G., Makris, Y.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.02.2008 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Alternate testing analog circuits Analog integrated circuits Circuit testing Confidence Costs Crosstalk Devices Digital integrated circuits Engineering Sciences Errors Machine learning Micro and nanotechnologies Microelectronics Neural networks Noise measurement Performance evaluation Radio frequencies Radio frequency Radiofrequency integrated circuits RF circuits Specifications Studies Test methods circuit testing analog circuits machine learning alternate testing RF circuits analog-circuits circuits testing
ISSN:	0278-0070, 1937-4151
Online-Zugang:	Volltext
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