Being able to record the electrical activities of a number of neurons simultaneously is likely
to be important in the study of the functional organization of networks of real neurons. Using
one extracellular microelectrode to record from several neurons is one approach to studying
the response properties of sets of adjacent and therefore likely related neurons. However, to
do this, it is necessary to correctly classify the signals generated by these different neurons.
This paper considers this problem of classifying the signals in such an extracellular recording,
based upon their shapes, and specifically considers the classification of signals in the case when
spikes overlap temporally
