Title :
Statistical identification of difference equation representations for nonlinear systems
Author_Institution :
Rogers, Bereskin & Parr, Toronto, Canada
Abstract :
A method is proposed for identifying a difference equation representation for a nonlinear system, by identifying a series of simpler difference equations. The method yields the difference equation representation which is optimal in the least-square sense, and applies to a wide variety of different inputs.
Keywords :
difference equations; identification; nonlinear systems; difference equation representations; identification; nonlinear systems; series of simpler difference equations; statistical identification;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19830121
