Truncated Moment Problem for Dirac Mixture Densities with Entropy Regularization
arXiv:1408.70834 citationsh-index: 44
Originality Synthesis-oriented
AI Analysis
For researchers in density estimation and moment problems, this provides a novel method for moment-matching with Dirac mixtures, though it is an incremental contribution building on existing moment-based approaches.
The paper addresses the problem of reconstructing a density from a finite set of moments, proposing an algorithm to compute Dirac mixture densities that preserve the given moments and ensure homogeneous state space coverage.
We assume that a finite set of moments of a random vector is given. Its underlying density is unknown. An algorithm is proposed for efficiently calculating Dirac mixture densities maintaining these moments while providing a homogeneous coverage of the state space.