Analog Test Interface for IEEE 1687 Employing Split SAR Architecture to Support Embedded Instrument Dependability Applications

2019 ◽  
Author(s):  
Jerrin Pathrose ◽  
Leon van de Logt ◽  
Hans G. Kerkhoff
Keyword(s):  
Analog Test

PARAMETRIC DEVIATION BASED ANALOG TEST AND DIAGNOSIS SYSTEM

2011 ◽  
Vol 20 (07) ◽  
pp. 1323-1340 ◽  
Author(s):  
KASTURI GHOSH ◽  
ARABINDA ROY ◽  
SEKHAR MONDAL ◽  
BAIDYANATH RAY
Keyword(s):  
Cellular Automata ◽  
Analog Circuits ◽  
Significant Enhancement ◽  
Performance Parameters ◽  
Analog Test ◽  
Diagnosis System ◽  
Response Data ◽  
Circuit Components ◽  
Diagnostic Resolution

This paper reports a comprehensive solution for the problem of test and diagnosis of OTA based analog circuits. Based on the parametric deviation of circuit components, a test and diagnosis methodology are proposed. Compressed signature generated out of multiple performance parameters has resulted in significant enhancement in fault diagnosing capability. The voluminous response data has been handled with Cellular Automata (CA) based classifier to achieve excellent diagnostic resolution.

scholarly journals Screening Using the SDQ Total Difficulties Scale: An Analog Test of Three Cutoff Values

2019 ◽  
Author(s):  
Tyler L Renshaw
Keyword(s):  
Well Being ◽  
The Self ◽  
Self Report ◽  
Future Research ◽  
Subjective Well Being ◽  
Analog Test ◽  
Research And Practice ◽  
Cutoff Values ◽  
Dependent Variables ◽  
Strengths And Difficulties

This brief report presents an analog test of the relative classification validity of three cutoff values (CVs; 16, 18, and 20) derived from responses to the self-report version of the Strengths and Difficulties Questionnaire: Total Difficulties Scale. Results from Bayesian t-tests, using several school-specific subjective well-being indicators as dependent variables, yielded evidence suggesting all CV models effectively differentiated between students with lower and higher levels of risk. Evidence also indicated that the lowest CV (16) was more effective than the higher CVs (18, 20) at identifying students with greater levels of risk, and that the higher CVs functioned comparably well. Implications for future research and practice are noted.

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