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A peek performance of 44.1 GOPS/W is achieved in the motion estimation application.
The SmartCell and the RaPid provide same throughput in motion estimation application, due to similar algorithm mapping structures.
Each step in the procedure involves a parameter estimation application for a given model structure and specific experimental data.
A hybrid state estimation application, a voltage monitoring application and a renewable energy integration application are implemented over this framework, as example of simulator usage.
In this real-time damage estimation application, the coefficient method (CM) defined in the FEMA-356 document (ASCE 2000) and later modified by ASCE/SEI 41-06 20077) was used.
In the view of above examples, there is no doubt that the presence of a real-time loss estimation application in metropolitan cities subject to earthquake hazards will provide immediate action and help to mitigate seismic risk during a potential future earthquake by providing rapid estimation of ground motion shaking maps and damage and loss assessments.
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Design of Kalman filter type and moving horizon estimators for on-line estimation applications based on first principles models is reviewed.
In location estimation applications, a more meaningful performance measure of location estimators is based on the geometric location estimation error ε = ( x ̂ − x k ) 2 + ( ŷ − y k ) 2. The mean-squared error (MSE) of any unbiased location estimator is lower bounded as (26) describes: ε rms 2 = E [ ( ε 2 ] ≥ [ F − 1 ] 11 + [ F − 1 ] 22, (27).
Optimal design and parameter estimation applications in sandwich structures are presented and discussed.
The Kalman filter has been widely used to solve different filtering problems especially in tracking and estimation applications.
Methods not shown include the Carroll method, the Sandell and Handtevy tapes (insufficient data) and neonatal weight estimation applications (out of scope).
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