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In addition to running these trackers on all unfoldings in parallel and recombining the signal subspace estimate via (10) or (11), the only modification we have to apply to the matrix-based subspace tracking schemes is the following: as introduced at the beginning of this section, it is typically assumed that the observation matrix X is augmented by a new column x(n) with each new snapshot n.
NPT is applied to the matrix with to get the NPT-transformed image A w.
The derivatization process is applied to the matrix and the molecular parameters are obtained by r.t.s.e.c.e.c
After calculating the AM-FM histograms, principal components analysis (PCA) was applied to the matrix containing histograms of the 120 ROIs (30 for each retinal structure) for three different AM-FM features: IA, IF magnitude (|IF|), and IF angle.
Spectral sparseness (SSP) is defined following [22] but is applied to the matrix W H. SSP assigns a high cost to nonzero bases assuming that the harmonic sounds can be represented as a set of overtones in the frequency.
Column permutations are then applied to the matrix in Figure 1b, generating the configuration presented in Figure 1c, which uncovers a visual data pattern whose identification was previously much harder to perceive.
Two-dimensional clustering algorithms were applied to the matrix.
Neighbor-joining is applied to the matrix to estimate the species tree topology using PHYBASE.
Then the progressive multi-alignment is applied to the matrix of pairwise alignment scores.
Hierarchical clustering with an average linkage method was applied to the matrix so as to arrange CGPs according to their network distances.
Similarly, Principal Component Analysis (PCA) is applied to the matrix of correlations of a set of variables to find a set of common underlying factors, called principal components [ 9].
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