Effects of Noise in Training Patterns on The Memory Capacity of The Fully Connected Binary Hopfield Neural Network : Mean-Field Theory and Simulations  

Oleh:

Wang, L.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 9 no. 4 (1998), page 697-704.
Topik: full 2D simulations; noise; training patterns; memory capacity; binary hopfield; neural network; mean - field theory; simulations

Ketersediaan

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

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Isi artikel

We show that the memory capacity of the fully connected binary Hopfield network is significantly reduced by a small amount of noise in training patterns. Our analytical results obtained with the mean field method are supported by extensive computer simulations.

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