For convenience, we denote the coinfection of multiplicity l as i 1 i 2 ⋯ i l, here i 1, i 2,…, i l ∈ H ≡ {1,2, 3,…, n} and i 1 < i 2 < ⋯< i l representing the strains present in the coinfection, which is independent of order of such infections.
$$\end{document} Here, I L is the left RGB image of the stereo camera system and z is the computed depth map.
In this instance the latency period and exposure window vary from one individual to another and we write: Here Δ i, L and Δ i, E are the latency period and exposure windows for the ith individual.
I'll spell it with one "L" here as a concession to the Americans.
Here, each interaction I l is indeed a sequence because the algorithm needs to know the exact number of t-tuples and hence position matters.
Here, since h i, l l = 0 L i − 1 are independent zero-mean CSCG random variables, we have E h i, l 2 = E h i, l ∗ 2 = 0 for all l, E h i, l h i, l ′ = E h i, l E h i, l ′ = 0 for l ≠ l′, and E h 1, l h 2, l ′ = E h 1, l E h 2, l ′ = 0 for all l and l′.
We assume here that the coefficients Y i, l ( l ∈ { 1, …, m } ) cannot be smooth simultaneously at the same point (i.e., Y i, l = 1 ⇒ Y i, l ′ ≠ 1 for l ≠ l ′ and fixed i ∈ { 1, …, n − 1 } ).
We get the problem analogous to (13), and here we must get one more real constant L 2. After solution of this problem, we get the function Φ in the form Φ ( z ) = Φ 0 ( z ) + i L 0 z + ( L 1 + i L 2 ) (24). in the grid points, here L 0, L 1, L 2 are the real constants.
Here, Δ i = a i i u + b i u M j ( M + 1 ) k j u r i l − a i j u M j.
Consider (5) shimmer (l ) = (1 / (N − 1 ) ) ∑ i = 1 N − 1 | A i, l − A i + 1, l | (1 / N ) ∑ i = 1 N A i, l, HNR: HNR employed here is calculated based on the residuals obtained by long-term predictive analysis [ 7, 8].
