New Dynamical Optimal Learning for Linear Multilayer FNN  

Oleh:

Tan, K. C. ; Tang, H. J.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 6 (Nov. 2004), page 1562-1569.
Topik: LINEAR; multilayer networks; dynamical; optimal learning; linear multilayer; FNN

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.11 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This letter presents a new dynamical optimal learning (DOL) algorithm for three - layer linear neural networks and investigates its generalization ability. The optimal learning rates can be fully determined during the training process. The mean squared error (mse) is guaranteed to be stably decreased and the learning is less sensitive to initial parameter settings. The simulation results illustrate that the proposed DOL algorithm gives better generalization performance and faster convergence as compared to standard error back propagation algorithm.

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