The composite regressor algorithm

Abstract

A relation between equation error and output-error adaptive algorithms is presented. It leads to a clarified view of output-error bias and stability. It is shown that a tradeoff between desirable stability and bias characteristics can be achieved in output error by manipulation of the adaptive gain. The composite regressor algorithm (CRA) is introduced as a means of affecting this tradeoff, independent of the gain. Output error is shown to a special case of CRA. A stability constraint for CRA is developed in a theorem, and the bias properties of this algorithm are discussed.<>