The breakdown point refers to the proportion of incorrect data that can be present in a dataset before the results of a state estimation become unreliable or invalid. This concept is particularly important in bad data detection, as it helps determine how resilient a state estimation algorithm is to inaccuracies in the input data. A higher breakdown point indicates that the algorithm can tolerate more bad data before the quality of the output is compromised.
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