A General Solution to the System Identification Problem Using Intermediate Domain Processing

摘要

This paper describes a general solution to the system identification problem. The technique is referred to as 'intermediate domain processing' and can result in faster and more efficient computations. The paper begins by outlining a general theory of translation-invariant linear systems. By making specific choices within this general framework, different special cases can be derived. A method is developed which facilitates the conversion between data vectors associated with each of these special cases. This conversion technique isused in deriving a generalized solution to the system identification problem. A practically useful example is considered in which the unknown system is assumed to be time-invariant linear (TIL), whereas computations are caried out in the domain of an equivalent and computationally advantageous dyadic-invariant linear (DIL) system.