Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
Volume 26, Issue 12, Pages 3227-3238Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNNLS.2015.2441697
Keywords
Complex-valued projection neural network; constrained optimization with complex variables; convergence analysis
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Funding
- National Natural Science Foundation of China [61179037, 61473330]
- Doctoral Project through the Ministry of Education, China [20133514110010]
- Research Grants Council through the Hong Kong Special Administrative Region [CUHK416812E]
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In this paper, we present a complex-valued projection neural network for solving constrained convex optimization problems of real functions with complex variables, as an extension of real-valued projection neural networks. Theoretically, by developing results on complex-valued optimization techniques, we prove that the complex-valued projection neural network is globally stable and convergent to the optimal solution. Obtained results are completely established in the complex domain and thus significantly generalize existing results of the real-valued projection neural networks. Numerical simulations are presented to confirm the obtained results and effectiveness of the proposed complex-valued projection neural network.
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