Unbiased identification of multivariable systems subject to colored noise

It is known that how to draw much more useful information from available sample data with a view to arriving at desired results is an important issue in system identification. A valuable new way of taking advantage of signal processing techniques to implement unbiased parameter was reported in [2]. In this paper, some important extensions to the recently developed bias-eliminated least-squares method [2] are made such that the method can be employed to perform unbiased identification of multi-input single-output systems subject to colored noise. The performance of the developed method is both analyzed theoretically and illustrated by means of some simulated examples.