This work proposes a strategy to adjust the combination weights of an adaptive network in order to attain both faster convergence during the transient phase and lower mean-square-error during the steady-state phase. Optimal combination weights are designed for both phases, and a procedure for detecting the transition from one phase to the other is also described. Simulation results illustrate the operation of the proposed strategy.