Modified discrete iterations for computing the inverse and pseudoinverse of the time-varying matrix

被引:32
|
作者
Petkovic, Marko D. [1 ]
Stanimirovic, PredragS. [1 ]
Katsikis, Vasilios N. [2 ]
机构
[1] Univ Nis, Fac Sci & Math, Visegradska 33, Nish 18000, Serbia
[2] Natl & Kapodistrian Univ Athens, Dept Econ, Div Math & Informat, Sofokleous 1 St, Athens 10559, Greece
关键词
Zhang neural network; Inverse matrix; Moore-Penrose inverse; Multi-step methods; ZHANG NEURAL-NETWORK; ZNN MODELS; COMPLEX ZFS; DIFFERENTIATION; APPROXIMATION; REPRESENTATION; ALGORITHMS;
D O I
10.1016/j.neucom.2018.02.005
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The general discretization scheme for transforming continuous-time ZNN models for matrix inversion and pseudoinversion into corresponding discrete-time iterative methods is developed and investigated. The proposed discrete-time ZNN models incorporate scaled Hyperpower iterative methods as well as the Newton iteration in certain cases. The general linear Multi-step method is applied in order to obtain the proposed discretization rule which comprises all previously proposed discretization schemes. Both the Euler difference rule and the Taylor-type difference rules are included in the general scheme. In particular, the iterative scheme based on the 4th order Adams-Bashforth method is proposed and numerically compared with other known iterative schemes. In addition, the ZNN model for computing the time-varying matrix inverse is extended to the singular or rectangular case for the pseudoinverse computation. Convergence properties of the continuous-time ZNN model in the case of the Moore-Penrose inverse and its discretization are also considered. (C) 2018 Published by Elsevier B.V.
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页码:155 / 165
页数:11
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