Search results
29 mar 2014 · If you are looking for the most efficient way of computation - use SciPy's cdist() (or pdist() if you need just vector of pairwise distances instead of full distance matrix) as suggested in Tweakimp's comment.
20 maj 2014 · Side note: Euclidean distance is not TOO bad for real-world problems due to the 'blessing of non-uniformity', which basically states that for real data, your data is probably NOT going to be distributed evenly in the higher dimensional space, but will occupy a small clusted subset of the space.
The topic of rank mini-mization for Euclidean distance matrix problems is discussed in, for example, [34, 35, 55, 56, 99, 100]. Graph realization and graph rigidity. The complexity of graph realization in a fixed dimension was determined to be NP-hard by [103, 119].
1 sty 2011 · Given a partially specified symmetric matrix A with zero diagonal, the Euclidean distance matrix completion problem (EDMCP) is to determine the unspecified entries to make A an EDM.We...
For examples of applications requiring solutions of EDM problems with different complications, see Figure 1. There are two fundamental problems associated with distance geometry [10]: 1) given a matrix, determine whether it is an EDM and 2) given a possibly incomplete set of distances, determine
What can we know about the underlying points that the distance information purports to describe? We also ask what it means when given distance information is incomplete; or suppose the distance information is not reliable, available, or specified only by certain tolerances (affine inequalities).
26 lut 2015 · We show how various EDM properties can be used to design algorithms for completing and denoising distance data. Along the way, we demonstrate applications to microphone position calibration, ultrasound tomography, room reconstruction from echoes and phase retrieval.
