Neighborhood Based Levenberg-Marquardt Algorithm for Neural Network Training  

Oleh:

Lera, G. ; Pinzolas, M.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 13 no. 5 (2002), page 1200-1203.
Topik: NEIGHBORHOOD; neighborhood; levenberg - marquardt

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.7A Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Although the Levenberg - Marquardt (LM) algorithm has been extensively applied as a neural - network training method, it suffers from being very expensive, both in memory and number of operations required, when the network to be trained has a significant number of adaptive weights. In this paper, the behaviour of a recently proposed variation of this algorithm is studied. This new method is based on the application of the concept of neural neighborhoods to the LM algorithm. It is shown that, by performing an LM step on a single neighborhood at each training iteration, not only significant savings in memory occupation and computing effort are obtained, but also, the overall performance of the LM method can be increased.

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