In the first input phase,
KBCC sets up a pool of recruitment candidates which include previously
learned source networks as well as single hidden units. There are several
versions of each candidate, each with a different set of initially randomized
connection weights from the input units (represented here by the dashed
arrow). As in ordinary cascade-correlation, the output weights are
temporarily frozen, represented here by the solid arrow.