Definition: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Input: <lb>This paper addresses the problem of ad hoc microphone array calibration where only partial<lb>information about the distances between microphones is available. We construct a matrix<lb>consisting of the pairwise distances and propose to estimate the missing entries based on a novel<lb>Euclidean distance matrix completion algorithm by alternative low-rank matrix completion and<lb>projection onto the Euclidean distance space. This approach confines the recovered matrix to the<lb>EDM cone at each iteration of the matrix completion algorithm. The theoretical guarantees of<lb>the calibration performance are obtained considering the random and locally structured missing<lb>entries as well as the measurement noise on the known distances. This study elucidates the links<lb>between the calibration error and the number of microphones along with the noise level and the<lb>ratio of missing distances. Thorough experiments on real data recordings and simulated setups<lb>are conducted to demonstrate these theoretical insights. A significant improvement is achieved<lb>by the proposed Euclidean distance matrix completion algorithm over the state-of-the-art<lb>techniques for ad hoc microphone array calibration.

Ad Hoc Microphone Array Calibration: Euclidean Distance Matrix Completion Algorithm and Theoretical Guarantees