The least squares algorithm, parametric system identification and bounded noise

The least squares parametric system identification algorithm is analyzed assuming that the noise is a bounded signal. A bound on the worst-case parameter estimation error is derived. This bound shows that the worst-case parameter estimation error decreases to zero as the bound on the noise is decreased to zero.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30503/1/0000132.pd