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Synthesis for symmetric weight matrices of neural networks

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2 Author(s)
Saubhayana, M. ; Dept. of Electr. & Comput. Eng., Maryland Univ., College Park, MD, USA ; Newcomb, R.W.

A synthesis method to guarantee symmetric weight matrices for a class of neural networks (which includes the Hopfield neural network as a special case) is proposed. This fills in a gap in the Li-Michel-Porod's synthesis and guarantees asymptotic stability for a given set of linearly independent equilibrium points under Lyapunov's stability criteria.

Published in:

Circuits and Systems, 2003. ISCAS '03. Proceedings of the 2003 International Symposium on  (Volume:5 )

Date of Conference:

25-28 May 2003