| 摘要 |
Echo state network (ESN), a novel recurrent neural network, has a randomly and
sparsely connected reservoir. Since the output weights are computed by Moore-Penrose inverse,
the ill-posed problem may exist in the ESN. To overcome this problem, ridge regression echo
state network (RESN) is proposed, in which the ridge regression algorithm is used to calculate
the output weights instead of linear regression. Simulation results show that the RESN has
better performance than some other existing methods, thus can deal with the ill-posed problem |