Recurrent neural network for computing the W-weighted Drazin inverse

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• 作者：Xue-Zhong Wang^a ; ^{xuezhongwang77@126.com} ; Haifeng Ma ; ^b ; ^{haifengma@aliyun.com} ; Predrag S. Stanimirović^c ; ^{pecko@pmf.ni.ac.rs}
• 关键词：Recurrent neural network ; W-weighted Drazin inverse ; Dynamic equation
• 刊名：Applied Mathematics and Computation
• 出版年：2017
• 出版时间：1 May 2017
• 年：2017
• 卷：300
• 期：Complete
• 页码：1-20
• 全文大小：2639 K
• 卷排序：300

文摘

Two gradient based recurrent neural networks (RNNs) for computing the W-weighted Drazin inverse of a real rectangular matrix are proposed and considered. Usage of the first RNN is limited by a specific constraint on the spectrum of a certain matrix. The second RNN is usable without restrictions. The stability of the recurrent neural networks as well as their convergence are considered. Numerical examples are given to show the efficiency of the proposed neural networks.