When error
reduction stagnates, a hidden unit is recruited. As the first hidden unit is
added, its input weights are frozen (shown in solid arrows), and training of
the output weights resumes.
CC networks are
generative in the sense that the learning algorithm builds the internal
topology of a network. Thus, CC networks grow as they learn.