Conditional Fuzzy Clustering in The Design of Radial Basis Function Neural Networks  

Oleh:

Pedrycz, W.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 9 no. 4 (1998), page 601-612.
Topik: radial basis function network; fuzzy clustering; design; radial basis function; neural networks

Ketersediaan

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

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Isi artikel

This paper is concerned with the use of radial basis function (RBF) neural networks aimed at an approximation of nonlinear mappings from Rn to R. The study is devoted to the design of these networks, especially their layer composed of RBF, using the techniques of fuzzy clustering. Proposed is an idea of conditional clustering whose main objective is to develop clusters (receptive fields) preserving homogeneity of the clustered patterns with regard to their similarity in the input space as well as their respective values assumed in the output space. The detailed clustering algorithm is accompanied by extensive simulation studies.

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