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Table 3 Entropy of some important distributions

From: Unified performance measures in network localization

Distribution PDF Entropy
Uniform [38] \(p(\theta) = \frac {1}{b-a}\) h=ld(ba)
Normal [38] \(p(\theta) = \frac {e^{(-{\theta }/{2\sigma ^{2}})}}{\sqrt {2\pi \sigma ^{2}}}\) \(h = \frac {1}{2} \text {ld}\left (2 \pi e \sigma ^{2} \right)\)
von Mises [39] \(p(\theta) = \frac {e^{\kappa \cos (\theta)}}{2\pi I_{0}(\kappa)}\) \(h = -\kappa \frac {I_{1}(\kappa)}{I_{0}(\kappa)} + \text {ld}\left (2\pi I_{0}(\kappa) \right) \)