Uncertainty-Based Non-Parametric Active Peak Detection

• URL: http://arxiv.org/abs/2205.02376v1
• Date: Thu, 5 May 2022 00:39:44 GMT
• Title: Uncertainty-Based Non-Parametric Active Peak Detection
• Authors: Praneeth Narayanamurthy and Urbashi Mitra
• Abstract summary: It is shown that under very mild conditions, the source localization error with $m$ actively chosen energy measurements scales as $O(log2 m/m)$. The proposed method enjoys superior performance on several types of data and outperforms the state-of-the-art passive source localization approaches.
• Score: 40.12401628262849
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Active, non-parametric peak detection is considered. As a use case, active source localization is examined and an uncertainty-based sampling scheme algorithm to effectively localize the peak from a few energy measurements is designed. It is shown that under very mild conditions, the source localization error with $m$ actively chosen energy measurements scales as $O(\log^2 m/m)$. Numerically, it is shown that in low-sample regimes, the proposed method enjoys superior performance on several types of data and outperforms the state-of-the-art passive source localization approaches and in the low sample regime, can outperform greedy methods as well.

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