Abstract
In this paper we present some of the basic ideas associated with the detection of abrupt changes in dynamic systems. Our presentation focuses on two classes of methods — multiple filter-based techniques and residual-based methods — and in far more detail on the multiple model and generalized likelihood ratio methods. Issues such as the effect of unknown onset time on algorithm complexity and structure and robustness to model uncertainty are discussed.
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