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The CQI indicates the channel quality identifier which expresses the quality of channels in terms of SIR. The quality of free channels can be computed by the expression given in [4] as Ψ n m = t n m G n n P n ∑ i ≠ n t m i G n i P i + σ n 2 (4).
A preliminary IRF was then computed by the expression where FFT and FFT−1 denote the Fast Fourier Transform and inverse Fast Fourier Transform, respectively.
It is computed by the expression shown below: (7) Classification _ Accuracy = CC N × 100, where N is the total number of the instances in the initial microarray dataset.
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The probability of the capacity of the integer system of (14), for a fixed time, can be computed by the formal expression wp(Lambda)= frac{theta}{sigma^{2}(Lambda)} exp biggl({ int frac{2mu(Lambda)}{sigma^{2}(Lambda)}, d Lambda} biggr), where θ is the normalized constant, nu=1, qquad tau= frac{theta}{sigma^{2}(Lambda)} quad text{and}quad Upsilon= intfrac{2mu(Lambda)}{sigma^{2}(Lambda)}, d Lambda.
From (8), the prediction coefficient set A K can be computed by the following expression, Rightarrow {A}^K={left[{displaystyle sum_{i=leftlceil frac{P}{2}rightrceil}^{L- Q}{U}_{2 i+1}^T}right{U}_{2 i+1}^Kright)}^T}right]}^{-1}{displaystyle sum_{i=leftlceil frac{P}{2}rightrceil}^{L- Q}{x}_{2 i+1}_{2_{2 i+1}_{2 (9).
We should notice that the sequence data stored in this database are computed by the regular expression-based approach named QGRS Mapper [ 17, 18].
The relative expression (also called fold change) of a gene in a particular tumor is computed by subtracting the expression of the gene in the tumor from the mean expression of the same gene in the reference sample set.
The sample covariance matrices can be computed by selecting the expression levels of the genes on the pathway and by computing the sample covariances.
This program calculates a Perturbation Factor for each gene, which is computed by normalising the expression ratio with information about its topology in the pathway (i.e., number of genes interacting with it and type of interaction) [ 19].
SMR are computed by the following mathematic expression: SMR=frac{{displaystyle sum_x{m}_x;.;{P}_x^{{displaystyle sum_x{P}_x^ (1).
The mean centroid of each leading-edge subset was computed by normalizing the expression levels of all subset genes to a mean of 0. Correlation analysis was performed as described later in Statistical Analysis.
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