Superposition of sigmoid function over a finite time interval is shown to be
equivalent to the linear combination of the solutions of a linearly
parameterized system of logistic differential equations. Due to the linearity
with respect to the parameters of the system, it is possible to design an
effective procedure for parameter adjustment. Stability properties of this
procedure are analyzed. Strategies shown in earlier studies to facilitate
learning such as randomization of a learning sequence and adding specially
designed disturbances during the learning phase are requirements for
guaranteeing convergence in the learning scheme proposed.Comment: 30 pages, 7 figure