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The experimental results verify the significant efficiency improvement of the proposed method in output quality and energy consumption, when compared with other fusion techniques in DCT domain.
Finally, in order to verify the theoretical results, the proposed method is applied to a fractional-order gyroscope model and computer simulations show the efficiency of the proposed method in output tracking.
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The proposed method in general outputs sparse binary matrices with optimal mutual coherence.
This permits the use of linear solution methods in the output layer, which can produce events as output, if modeled as a classifier – the output classes are "event" or "no event".
The simulation results of the proposed method were compared with SPWM and the conventional HIPWM-FMTC methods in the output voltage characteristics, rotor speed, and torque ripple.
The simulation results show the effectiveness of the proposed method in terms of output performance improvement and the computational burden.
The results from two test cases with different levels of measurement uncertainty show significant improvement of the BI-SVR approach over the regular SVR method in predicting various output measurements.
Blasting against available databases is the standard method, which results in outputs of large quantities and is therefore mainly used for annotation only (e.g., Parchman et al., 2010).
But the periodic perturbation in the method may produce unacceptable oscillations in output power, and its complicated penalty function will lead to long convergence time.
We assess the utility of these different methods in analyzing spatial output and comparing model output to data, and give recommendations for their appropriate use.
In this method output voltage of each stage in converter is defined as sum of the ideal product and error signal, which error voltage include of linear non-ideal section or first order error and nonlinearity undesired signal or third order error.
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