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A NEURAL-BASED NONLINEAR L1 OPTIMIZATION ALGORITHM FOR DIAGNOSIS OF NETWORKS |
He Yigang; Luo Xianjue; Qiu Guanyuan |
School of Electrical Engineering,Xi'an Jiaotong University,Xi'an 710049 |
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Abstract Based on exact penalty function, a new neural-networks for solving the L1-norm optimization problem is proposed. In comparison with Kennedy and Chua s networks(1988), it has better properties. Based on Bandler s fault location method(1982), a new nonlinearly constrained L1 norm problem is developed. It can be solved with less computing time through only one optimization processing. The proposed neural networks can be used to solve the analog diagnosis L1 problem. The validity of the neural networks and the fault location L1 method are illustrated by extensive computer simulations.
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Received: 30 June 1995
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