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Quantize the gap between two singular values.
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Among them, the eigengene 3 showed the smallest difference between the two singular values that it was associated with (Figure 1-B), suggesting that this eigengene had nearly equal contribution to the variance of human and mouse datasets.
The difference between the two singular values of an eigengene is measured by the angular distance (Eq. 4): <img src="http://journals.plos.org/plosone/article/asset?id=info?doi/10.1371/journal.pone.0003406.e005.PNG" class= inline-graphic"/> An angular distance of zero indicates an eigengene has equal contribution or significance to both datasets.
This is due to the difference between the first two singular values and the last singular value.
In this and a sequel paper (Combinatorial designs with two singular values. II. Partial geometric designs, preprint) we study combinatorial designs whose incidence matrix has two distinct singular values.
In this and an earlier paper [E.R. van Dam, E. Spence, Combinatorial designs with two singular values. I. Uniform multiplicative designs, J. Combin. Theory A 107 (2004) 127 142] we study combinatorial designs whose incidence matrix has two distinct singular values.
The correlation between GPS-TEC and IRI model data for the first three singular values is illustrated in Table 1.
V k (0) contains vectors corresponding to the zero singular values, and V k (1) consists of the singular vectors corresponding to nonzero singular values.
Matrices ( {tilde{mathbf{V}}}_i^{(1)} ) and ( {tilde{mathbf{V}}}_i^{(0)} ) denote the right singular matrices where each consists of the singular vectors corresponding to non-zero singular values and zero singular values, respectively.
The correlation coefficient for the first three singular values is more than 0.86.
Shown are the distributions of the five singular values of the ECM.NLOS office scenarioCafeteria scenario.
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