A Novel Neural Network for Nonlinear Convex Programming  

Oleh:

Gao, Xing-Bao

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 15 no. 3 (May 2004), page 613-621.
Topik: convex relation; novel neural network; non linear convex programming

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.10 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

In this paper, we present a neural network for solving the nonlinear convex programming problem in real time by means of the projection method. The main idea is to convert the convex programming problem into a variational inequality problem. Then a dynamical system and a convex energy function are constructed for resulting variational inequality problem. It is shown that the proposed neural network is stable in the sense of Lyapunov and can converge to an exact optimal solution of the original problem. Compared with the existing neural networks for solving the nonlinear convex programming problem, the proposed neural network has no Lipschitz condition, no adjustable parameter, and its structure is simple. The validity and transient behaviour of the proposed neural network are demonstrated by some simulation results.

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