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- 2018
求解具有约束的l1-范数问题的神经网络模型
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Abstract:
摘要： 提出了一个解约束最小 l1-范数问题的单层神经网络模型。与已有神经网络模型相比,提出的模型所需神经元数少且层数少。通过引入 Lyapunov 函数,证明了该模型的稳定性和收敛性。数值试验结果表明所提出的模型具有良好的性能。
Abstract: This paper presents a one-layer neural network model for solving l1-norm problems with constraints. Compared with some existing neural network models, the proposed model needs fewer neurons and has a simpler structure. The stability and convergence of the proposed model are proved by introducing a Lyapunov function. Some simulation examples are used to illustrate its validity and transient behaviors
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