Pattern detection using a maximal rejection classifier

Summary form only given. In target detection applications, the aim is to detect occurrences of a specific target in a given signal. In general, the target is subjected to some particular type of transformation, hence we have a set of target signals to be detected. In this context, the set of non-target samples are referred to as clutter. In practice, the target detection problem can be characterized as designing a classifier C(z), which, given an input vector z, has to decide whether z belongs to the target class X or the clutter class Y. In example based classification, this classifier is designed using two training sets -Xˆ={xi}_i=1..Lx (target samples) and Yˆ={y_i}_i=1..Ly (clutter samples), drawn from the above two classes