Time complexity and model complexity of fast identification

Abstract

Gel'fand and Kolmogorov n-widths are used to describe the time complexity and model complexity of an identification process, and inequalities relating these n-widths are obtained. The optimal n-parameter affine models for a class of a priori data sets are obtained through n-width estimation. A 'spectrum flatness' property of an input is shown to characterize its identifying capability.