Below, we adopt confusion matrix to demonstrate the overall system performance (see Table 5).
In order to mathematically characterize the interference-coupled network, we adopt the matrix notation and the system model used in recent works [1, 5].
To estimate the frequencies of all the sinusoids in the CFRs of the q-th AP, we adopt the matrix pencil method (MPM) [12, 13] because this constant amplitude multiple-sinusoid estimation problem is equivalent to the direction-of-arrival estimation problem with fully coherent sources, which is directly addressed by the MPM.
We adopt a similar Distributed Matrix to store the matrix L that is to be decomposed on HDFS, and the storage of matrix L on HDFS is according to segmentation.
We adopt the transmission matrix method to analyze the transmission properties of such reflectors and use the decimal genetic algorithm to obtain broad omnidirectional total reflection (ODTR) bandwidth.
Additionally, we adopt a precoding matrix comprising N−1 mutually orthonormal column vectors in ℂ N for a transmitter with N antennas, thereby having a different received SINR from that in [21].
We adopt the contact matrix formalism and the age classes defined by Wallinga and collaborators [ 42].
In this study, we adopt cross-power matrix [ 10] to reflect the spatial patterns of the brain.
For simplicity, in the subsequent analysis, we adopt the brain connectivity matrix generated from the combination sample using the median statistics (i.e. the panel in the lower right corner of Fig. 1). Figure 2 shows a network visualization of this matrix, where edges correspond to matrix entries with values ≥ 0.5 or ≤ − 0.5.
In order to implement a fast matrix assembly algorithm, we adopted the reduction list approach proposed in [26].
