Summary
Case-based reasoning (CBR) is used when generalized knowledge is lacking. The method works on a set of cases formerly processed and stored in the case base. A new case is interpreted based on its similarity to cases in the case base. The closest case with its associated result is selected and presented as output of the system. Signal-interpreting systems for 1-d, 2-d, or 3-dimensional signals are becoming increasingly popular in medical and industrial applications. New strategies are necessary that can adapt to changing environmental conditions, user needs, and process requirements. Introducing CBR strategies into signal-interpreting systems can satisfy these requirements. We describe in this chapter the basics of CBR and review what has been done so far in the field of signal-interpreting systems.