Sentence examples for using the approximation in from inspiring English sources

It is worth noting that beside maximizing the sum-rate, the problem of maximizing the individual rate using the approximation in (16) has the same solution obtained in (22).

Using the approximation in (25), it can be noted that the mean value of (boldsymbol {W}_{bar {u}}[w]), i.e. ({E}{ boldsymbol {W}_{bar {u}}[w] }), is begin{array}{*{20}l} {E}left{ boldsymbol{W}_{bar{u}}[w] right} &= frac{1}{mathcal{W}^{mathcal{^{mathcal{W}-1} boldsymbol{W}_{bar{u}}[w] &approx 1 left/ mathcal{W}right.

(8) and (9) by using the approximation in Eq. (10) for t′=100, we obtain the incidences λ0 and λ1 as shown Fig. 7.

For the k-fold scheme, the accuracy computed using the approximation in (14) gave an estimate that was higher than one (1.04).

To solve the linear complementarity problem (28), we carry out a discretisation of ∂V ∂ τ ∗ − L r V = 0 Open image in new window similar to the discretisation carried out for (23) using the approximations in (24).

The ODE (Eq. (19)) was simulated using the approximations in Eqs.

We use the approximation in (12).

In this calculation, we use the approximation in the denominators as geometrical spreading factors, because the noise sources are distributed in the far field, R ≫ D. We also approximate the distance in the exponent, and, where.

Instead, we use the approximation in (20) and model the aggregated noise as a normally distributed random variable such that (widetilde {v}_{m}[n] sim mathcal {N}left ({sigma _{m}^{2}}, bar {sigma }_{m}^{2}right)).

For the calculation of the SU throughput in simulation, we used the approximation in [25], tight within 1 dB for M≥4 and BER≤10−3 as begin{array}rcl@ Cleft (text{SINR} right)approx text{BW}_{text{ch}} log_{2} left [1+frac{text{SINR}}{-ln big 5 text{BER}big)/1.6 }right ], end{array} (19).

We note that (30) can be evaluated using the approximation as in (15) after substituting f ov with m and p fa with α.