A Fuzzy - Controlled Delta - Bar - Delta LearningruleW
نویسنده
چکیده
| In classic backpropagation nets, as introduced by Rumelhart et al. 1], the weights are modiied according to the method of steepest descent. The goal of this weight modiication is to minimise the error in net-outputs for a given training set. Basing upon Jacobs' work 2], we point out drawbacks of steepest descent and suggest improvements on it. These yield a backpropagation net, which adjusts its weights according to a parallel coordinate descent method, whose parameters are being fuzzy-controlled.
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