We investigate the most effective identification approach of a vehicle model by experimental data.
We are confronted by two difficulties: making the quantitative model on the human response time with the similarity and validating the proposed model by experimental work.
Fabrication and RF characterization of GaN HEMT on silicon and sapphire substrate are done, and henceforth, forming a Verilog-A model by experimental results obtained from RF characterization of GaN HEMT.
Finally, we compare our method with several recent state-of-the-art methods and illustrate the efficiency and performance of the proposed model by experimental results in peak signal to noise ratio (PSNR) and computing time.
The entirely theoretical model by Fussenegger et al. was followed by a number of ODE-based models supported by experimental data.
After residual generation, statistical change detection scheme is derived from mathematical models supported by experimental data.
We annotate all transcript models supported by experimental evidence, predominantly ESTs and mRNAs.
The research consists of analytical modeling verified by experimental results.
It is carried out by evaluating the mechanical strength modeled both by experimental and numerical methods.
In the present work, we are studying the inhibition of the serotonin transporter protein by a series of buspirone analogues by molecular modelling and by experimental affinity measurements.
