A Successive Overrelaxation Backpropagation Algorithm for Neural-Network Training  

Oleh:

Merelli, E. ; Capparuccia, R. ; De Leone, R.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 9 no. 3 (1998), page 381-388.
Topik: ALGORITHM; successive; overrelaxation; backpropagation; algorithm; neural - network training

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.3 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

A variation of the classical backpropagation algorithm for neural network training is proposed, and convergence is established using the perturbation results of Mangasarian and Solodov (1994). The algorithm is similar to the successive overrelaxation (SOR) algorithm for systems of linear equations and linear complementary problems in using the most recently computed values of the weights to update the values on the remaining arcs.

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