STRIP - A Strip-Based Neural-Network Growth Algorithm for Learning Multiple-Valued Functions  

Oleh:

Stojmenovic, I. ; Milutinovic V. ; Ngom, A.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 12 no. 2 (2001), page 212-227.
Topik: NEURAL NETWORKS; strip - based; neural - network; algorithm; multiple - valued; functions

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.5 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

We consider the problem of synthesizing multiple - valued logic functions by neural networks. A genetic algorithm (GA) which finds the longest strip in V?Kn is described. A strip contains points located between two parallel hyperplanes. Repeated application of GA partitions the space V into certain number of strips, each of them corresponding to a hidden unit. We construct two neural networks based on these hidden units and show that they correctly compute the given but arbitrary multiple - valued function. Preliminary experimental results are presented and discussed.

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