The adaptive cross approximation (ACA) algorithm has been used in many fast Integral Equation solvers for electromagnetic Radiation and Scattering problems. It efficiently computes a low rank approximation to the interaction matrix between mutually distant parts of a scattering object. The ACA is an iterative algorithm that needs an accurate and efficient convergence criterion. The evaluation of this criterion may consume a considerable part of the computational resources. This communication presents an efficient new way to evaluate the convergence criterion, using a stochastic approach.
CitationHeldring, A.; Ubeda, E.; Rius, J. Stochastic estimation of the Frobenius norm in the ACA convergence criterion. "IEEE transactions on antennas and propagation", 01 Març 2015, vol. 63, núm. 3, p. 1155-1159.
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