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Let us now evaluate the increment of the cost generated by the multi-watermark-based detector, Δ J m, and next, compare the cost generated by the single- and the multi-watermarks.
As a result, we have the following inequality for the increment of the cost functional: Delta J_{varepsilon }bigl u_{varepsilon }^{0},y_{varepsilon }^{0} bigr):=J_{varepsilon }bigl u_{varepsilon }^{lambda},y_{varepsilon }^{lambda}bigr -J_{varepsilon }bigl(u_{varepsilon }^{lambda}bigr -J_{varepsilonr)ge0,quadforall lambdainmathbb{R}bigl u_{varepsilon
Similar(57)
Note that the increment of x factors involves an exponential increment of the computational cost.
In this section, we compute the increment of cost in the LQG structure due to the single-watermark added to the control input.
where J ∗ is the optimal cost of the system described in Section 3.1; and Δ J s is the increment of cost due to the use of the single-watermark-based detector.
Secondly, the increment of computational cost is focused on generating the discriminative language characterization score vectors.
However, the increment of energy cost caused by equipping a carbon capture process is the main barrier to its commercial deployment.
Then, the total cumulative cost increment of the HEN, including the increment of utility costs and equipment investment costs, is regarded as the objective function.
Echo/anti-echo based schemes can be implemented easily by applying pulsed field gradients during evolution 15 requiring only two FIDs per time increment but at the cost of irreversibly defocusing the complimentary component in each transient, that is, discarding 50%% of useful signal, thus losing ca. 30%% of the per scan signal-to-noise ratio.
Δ J s : Increment of quadratic cost due to the single-watermark.
Δ J m : Increment of quadratic cost due to the multi-watermark.
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