Qualitative analysis of a recurrent neural network for nonlinear continuously differentiable convex minimization over a nonempty closed convex subset

IEEE Transactions on Neural Networks

Volumn 12, Issue 6, 2001, Pages 1521-1525

  Liang, X B ^a  

^a UNIVERSITY OF DELAWARE   (United States)

Author keywords

Closed convex subsets; Convex minimization; Global convergence; Global existence of solutions; Global exponential convergence; Recurrent neural networks (RNNs); Uniform convexity

Indexed keywords

ASYMPTOTIC STABILITY; COMPUTER SIMULATION; LYAPUNOV METHODS; OPTIMIZATION; QUADRATIC PROGRAMMING; SET THEORY; THEOREM PROVING;

CLOSED CONVEX SUBSETS; CONVEX MINIMIZATION; GLOBAL CONVERGENCE; GLOBAL EXPONENTIAL CONVERGENCE; UNIFORM CONVEXITY;

RECURRENT NEURAL NETWORKS;

EID: 0035506173     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.963790     Document Type: Letter

References (11)

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5. A recurrent neural network for nonlinear continuously differentiable optimization over a compact convex subset
6. Finite-dimensional variational inequality and nonlinear complementary problems: A survey of theory, algorithms, and applications
7. A posterior error bounds for the linearly constrained variational inequality problem