Based on assumption (3), LAItree is linearly related to tree height (H tree) for each species.
Based on Assumption 6, we define, as the transmit power when a user's channel gain is.
Based on assumption (A2) and (5.4), we obtain the following inequality by applying Lemma 4.1: (59).
Based on assumption, the utility can be divided into systematic and random parts (shown in Eq. 2).
Based on assumption (4), if ( k_{text{mt,A}} ll k ) in the initial reaction period: k_{text{app}} = k_{text{mt,A}} (12).
Based on Assumption A.1), it can be easily shown that x nk is a Bernouli RV with the parameter begin{array}rcl@ p = P(x_{nk}=1) = 1-e^{-frac{T_{s}}{mu}}.
Based on assumption 2, we expect most λ ij ≈ 0. A normal distribution with a fixed variance parameter is not sufficient to impose this constraint.
Based on assumption 1, we expect that few factors will be sufficient to explain total phenotypic variation, and thus { τ j} will increase rapidly.
Based on Assumption 1 below our paper provides a combinatorial framework for quantifying the effects of sparsification of the Λ∗ rule.
Most existing aeroelastic models are linear models based on assumption of small blade deflections.
Results based on assumption of homogeneous and inhomogeneous distribution of nanoparticles are compared with each other.
