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首页> 外文期刊>Neural Networks and Learning Systems, IEEE Transactions on >A Complex-Valued Projection Neural Network for Constrained Optimization of Real Functions in Complex Variables
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A Complex-Valued Projection Neural Network for Constrained Optimization of Real Functions in Complex Variables

机译：复杂变量实函数约束优化的复值投影神经网络

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摘要

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.
机译：在本文中，我们提出了一种用于解决具有复杂变量的实函数的约束凸优化问题的复值投影神经网络，作为对实值投影神经网络的扩展。从理论上讲，通过开发复值优化技术的结果，我们证明了复值投影神经网络是全局稳定的，并且收敛于最优解。在复杂域中完全建立了获得的结果，从而显着地推广了实值投影神经网络的现有结果。数值模拟被提出来确认所获得的结果和所提出的复值投影神经网络的有效性。

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