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A recurrent neural network for equality constrained optimization problems is proposed, which makes use of a cost gradient projection onto the tangent space of the constraints. The proposed neural network constructs a generically non-feasible trajectory, satisfying the constraints only as t /spl rarr/ /spl infin/. Generalized convergence results are given(More)
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