• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.532-534
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• 1990

We suggest a new energy function that improves the area complexity of the Hopfield Crossbar Network. Through converting data representation to an encoded format, we reduce the number of nodes of the network, and thus reduce the entire size. We apply this approach to the layer assignment problem, and use the modified delayed self-feedback Hopfield Network. Area complexity of the existing network for layer assignment ploblem is improved from O( $N^2L^2$ ) to O($N^2$(log L)$^2$).

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.1
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• pp.26-30
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• 2000

Switching of the transmission lines(T/L) is one of the methods for wuppressing the short circuit capacity. This paper presents the T/L switching operation by using the Hopfield neural network(HNN). The switching of T/L can make the line powers and the bus voltages deteriorated, as well as the fault current decreased. Such an insecure state should be avoided when the T/L is operated to be open. In this studies, the inequality constraints are formulated into the objective function to be incorporated with the HNN. Test results show that the convergence characteristics of HNN lead to the adequate solution of T/L switching.