Analytical Modelling of Power Attenuation under Parameter Fluctuations with Applications to Self-Test and Repair

Kadim, H.J.

doi:10.1109/ahs.2006.24

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Cited by 7 publications

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“…This is desirable for many reasons, but mainly because tests on the real system may be costly or impractical. The modelling expressions developed can also be used to predict changes in the measurand (or the sensed medium) [23]. …”

Section: Resultsmentioning

confidence: 99%

Parameter Modelling Approach with Potential Applications for Self-Test of Biosensors

Kadim

2008

2008 NASA/ESA Conference on Adaptive Hardware and Systems

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Establishing a relationship between the measurand and key parameters affecting the propagated light in a waveguide provides useful information for functional verification and testing of optical biosensors. The proposed mathematical model can estimate the expected responses which -independent of the sensor operation -can be compared against the measured responses to identify inconsistencies in the sensor performance. A noticeable drift in the estimated light intensity from that measured at the detector is an indication of abnormality in the sensor's functionality.

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Section: Resultsmentioning

confidence: 99%

Parameter Modelling Approach with Potential Applications for Self-Test of Biosensors

Kadim

2008

2008 NASA/ESA Conference on Adaptive Hardware and Systems

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State-Space Based Analytical Modelling for Real-Time Fault Recovery and Self-Repair with Applications to Biosensors

Kadim

2006

First NASA/ESA Conference on Adaptive Hardware and Systems (AHS'06)

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Predictive Analysis for Robust Operation with Applications to Autonomous Biosensors

Kadim¹

2007

Second NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2007)

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Analytical Modelling of Power Attenuation under Parameter Fluctuations with Applications to Self-Test and Repair

Cited by 7 publications

References 9 publications

Parameter Modelling Approach with Potential Applications for Self-Test of Biosensors

Parameter Modelling Approach with Potential Applications for Self-Test of Biosensors

State-Space Based Analytical Modelling for Real-Time Fault Recovery and Self-Repair with Applications to Biosensors

Predictive Analysis for Robust Operation with Applications to Autonomous Biosensors

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