Focusses on filtering for linear processes, and helps design linear
stable unbiased filters that yield an estimation error with the
lowest root-mean-square (RMS) norm. This book defines various
hierarchical classes of filtering problems based on the
availability of statistical knowledge regarding noise,
disturbances, and other uncertainties.
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