A Complex Gradient Neural Dynamics for Fast Complex Matrix Inversion

被引：3

作者：

Xiao, Lin ^{[1
]}

Liao, Bolin ^{[1
]}

Zeng, Qinli ^{[1
,2
]}

Ding, Lei ^{[1
]}

Lu, Rongbo ^{[1
]}

机构：

[1] Jishou Univ, Coll Informat Sci & Engn, Jishou 416000, Peoples R China

[2] Sun Yat Sen Univ, Sch Elect & Informat Technol, Guangzhou 510275, Guangdong, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS, PT I | 2017年 / 10261卷

基金：

中国国家自然科学基金;

关键词：

Complex-valued matrix inversion; Theoretical analysis; Complex domain; Neural dynamic model; FINITE-TIME SOLUTION; NETWORK; DESIGN; EQUATION; SCHEME; MODEL;

D O I：

10.1007/978-3-319-59072-1_61

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Complex-valued matrix inversion problem is investigated by using the gradient-neural-dynamic method. Differing from the traditional processing method (only for real-valued matrix inversion), the proposed method develops a complex gradient neural dynamics for complex-valued matrix inversion in the complex domain. The advantages of the proposed method decrease the complexities in the aspects of computation, analysis, and computer simulations. Theoretical discussions and computer simulations demonstrate the efficacy and superiorness of the proposed method for online the complex-valued matrix inversion in the complex domain, as compared to the traditional processing method.

引用

页码：521 / 528

页数：8

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