“…According to this property, called asymptotic normality, the well-known criterion AIC (Akaike information criterion; Akaike, 1974) is derived. In the case of MLP, however, we cannot show the asymptotic normality of estimators because of the unidentifiability of optimal parameters, so that the effectiveness of AIC is not ensured (Hagiwara, Toda, & Usui, 1993;Anders & Korn, 1999). Although some other criteria, such as NIC (network information criterion; Murata, Yoshizawa, & Amari, 1994) and GPE (generalized prediction error; Moody, 1992), have been proposed for MLP, they are effective only when the asymptotic normality holds.…”