Sentence examples for maximizing the terms from inspiring English sources

Since the optimum solution does not yield a closed-form expression, we proposed a suboptimal scheme by sequentially maximizing the terms in the integrand of the lower bound.

Thus, maximizing the SNR at the receiver side is equivalent to maximizing the term ({|mathbf {g}^{H}mathbf {Hw}|_{F}^{2}}/{|mathbf {g}|_{F}^{2}}).

The typical variant of MaxPHYThru which we denote by MaxPHYThru-FER chooses the MCS maximizing the term ((1-fer_{m,s})log _{2}(V_{m}) R_{m}) [66].

Since ( {leftVert {Q}_crightVert}_F^2 ) and ( {leftVert {P}_crightVert}_F^2 ) are constant, the minimization of Eq. (6) is dominated by maximizing the term, tr(P c T Q c R T )).

It can be shown that the optimal codevector is the one maximizing the term Q k : Q k = x T H c k 2 c k T H T H c k = d c k 2 c k T Φ c k (2 where d = xTH, the correlation function, is expressed as d n = ∑ i = n L − 1 x i h i − n, 0 ≤ n ≤ L − 1 (3)where L is the speech subframe size.

The objective of spectral clustering is equivalent to maximizing the term as (11) Therefore, the objective of the KL integration can be rewritten in an additive form, given by (12) where A, G c are defined the same as in (8), κ is the free parameter to adjust the effect of kernel and Laplacian in KL integration.

Minimizing Equation (1) is equivalent to minimizing the first term while maximizing the second term.

The minimization is achieved by maximizing the second term in the above expression.

Consequently, EV charging optimization is equivalent to maximizing the (omega) term.

Hence, minimizing is equivalent to maximizing the second term of (15) which is redefined as follows: (16).

In this paper, we focus on maximizing the long-term secondary throughput by providing the secondary users two modes to choose at the start of each time slot.