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For this article, we have developed an effective analytical simulation methodology capable of simulating complex biophotonic sensing architectures.
The experimental results are compared to numerical and analytical simulation.
These behaviors are discussed and explained using an analytical simulation.
Results of preliminary analytical simulation work is also described.
In Figs. 9, 10 and 11, label "A" ("S") stands for analytical (simulation) results.
For our review, we divided methods into three groups: analytical, simulation, and combined.
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Included in this study are analytical, simulation-based, and experimental benchmarking approaches to consider five use cases for ERI sorting, i.e. SIMD processing, reconfigurable computing, limited address spaces, instruction cache exploitation, and data cache exploitation.
The proposed scheme is validated through analytical simulations and using a voice traffic model.
In the current study, the third approach based on extensive nonlinear analytical simulations is adopted.
As experimental studies are expensive and time consuming, analytical simulations are generally preferred.
Tip calibration and analytical simulations of these experiments have been performed using the finite element method.
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