However, as FAP 2 selects its beamforming vector to minimize interference to FUE 1, FUE 2 loses its coherent combining gain (moving back to the solid line), but FUE 1 gains from receiving less interference (dashed-dotted line).
Important biosafety features are also engineered into the lentiviral vector to minimize the probability of the assembly of recombinant competent HIV-1; the essential structural and functional proteins of the virus have been separated into individual expression plasmids.
This might be combined with cell lysis procedures, either chemically or by the use of an autolytic vector, to minimize biases by enzymatic breakdown of the gene product, toxicity or secretion problems.
As an opposite approach to MAX-SNR beamforming strategy, each BS can find the transmit beamforming vectors to minimize the generating interference to other users [8] by solving the following objective problem: w k, m ⋆ = arg min w k, m ∈ C M × 1 ∑ i = 1, i ≠ k M h i, m ∗ w k, m 2 + ∑ i = 1 M ∑ j = 1, j ≠ m L g i, j, m ∗ w k, m 2. (7).
Taking it all together, routine CHIK surveillance and vector control should be given due consideration in Southeast Asia and regions having tropical/sub-tropical weather that promotes the spread of CHIK vectors, to minimize and prevent the occurrence of outbreaks.
On training by back-propagation algorithm with v number of vectors (x_{l}^{(i)}), the AE updates its weight matrix (W_1) and bias vector B1, to minimize the reconstruction error (sum nolimits _{i=1}^vparallel x_{l}^{(i }-hat{x}_{l}^{(i }-hat{xel ^2).
Similar to the proof of Theorem 1, we are now proceeding to find a vector v̂ to minimize the energy function (J v)).
Then find a vector v̂ to minimize the following energy function (J v)): J v =sum_{i=-h+1}^{0}z(i)^{T}Rz(i).
Therefore, the estimation of edge direction can be formulated as the task of finding a unit vector d to minimize the following cost function: cost ( d ) = ∑ k = - k 0 k 0 ∑ l = - l 0 l 0 d T · g ( k, l ) 2 = d T · ∑ k = - k 0 k 0 ∑ l = - l 0 l 0 g ( k, l ) · g T ( k, l ) · d = d T C d, (21).
The equality of polynomial matrix and dft matrix decomposed matrices decompositions are guaranteed via the finite duration constraint, which is investigated in Section 4. The finite duration constraint imposes the phase angles of singular vector (eigenvector) to minimize a nonlinear quadratic function.
The penalized constrained least squares with monotonicity constraint are used to evaluate the parameter vector β, to minimize (7) || Y − X β || 2 + λ β T S β.
