The correlation-domain recursive least-squares algorithms for identification

A version of recursive least-squares (RLS) adaptive algorithms, correlation-domain recursive least-squares (CDRLS) algorithms, is presented for identification applications using two correlation vectors to track the information. It is shown that in the CDRLS, various data windows can be manipulated simply by adjusting the correlation vectors in different ways, leading to the flexibility in exact initialization and real-time variation of the window length. In addition, the CDRLS is block-processing applicable and numerically stable. Two typical identification illustrations are provided.<>