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# Table 2 Comparison of LV-OBS (*Φ*) with the greedy algorithms that minimize the entropy function of (Chen et al. 2014) (*Φ*
_{
ent
}) and the expected distance (*Φ*
_{
dist
})

From: The effect of transmission variance on observer placement for source-localization

\(\rho (\mathcal {P}_{s}, \Phi, \Phi _{dist})\) | \(\rho (\mathcal {D}, \Phi _{dist}, \Phi)\) | \(\rho ({\mathcal P_{s}}, \Phi, \Phi _{ent})\) | |
---|---|---|---|

Random Geometric Network, N=100, r=0.2
| |||

k=2
| -0.205 | 0.101 | -0.033 |

k=4
| -0.014 | -0.003 | -0.007 |

k=8
| -0.003 | -0.002 | -0.003 |

Barabàsi Albert Network, N=100, m=3
| |||

k=2
| -0.168 | 0.023 | -0.037 |

k=4
| -0.039 | 0.025 | -0.028 |

k=8
| -0.004 | -0.003 | 0.005 |