Fuzzy Auto-Associative Neural Networks for Principal Component Extraction of Noisy Data  

Oleh:

Yang, Tai-Ning ; Wang, Sheng-De

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 11 no. 3 (2000), page 808-810.
Topik: networks; fuzzy; auto - associative; neural networks; principal component; extraction; noisy data

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.4 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

In this paper, we propose a fuzzy auto - associative neural network for principal component extraction. The objective function is based on reconstructing the inputs from the corresponding outputs of the auto - associative neural network. Unlike the traditional approaches, the proposed criterion is a fuzzy mean squared error. We prove that the proposed objective function is an appropriate fuzzy formulation of auto - associative neural network for principal component extraction. Simulations are given to show the performances of the proposed neural networks in comparison with the existing method.

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