On The Problem of Spurious Patterns in Neural Associative Memory Models  

Oleh:

Athithan, G. ; Dasgupta, C.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 8 no. 6 (1997), page 1483-1491.
Topik: neural network; spurious patterns; neural associative; memory models

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.2 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

The problem of spurious patterns in neural associative memory models is discussed. Some suggestions to solve this problem from the literature are reviewed and their inadequacies are pointed out. A solution based on the notion of neural self - interaction with a suitably chosen magnitude is presented for the Hebbian learning rule. For an optimal learning rule based on linear programming, asymmetric dilution of synaptic connections is presented as another solution to the problem of spurious patterns. With varying percentages of asymmetric dilution it is demonstrated numerically that this optimal learning rule leads to near total suppression of spurious patterns. For practical usage of neural associative memory networks a combination of the two solutions with the optimal learning rule is recommended to be the best proposition.

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