2019
DOI: 10.1002/mma.5596
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Reflexive periodic solutions of general periodic matrix equations

Abstract: Analysis and design of linear periodic control systems are closely related to the periodic matrix equations. The objective of this paper is to provide four new iterative methods based on the conjugate gradient normal equation error (CGNE), conjugate gradient normal equation residual (CGNR), and least‐squares QR factorization (LSQR) algorithms to find the reflexive periodic solutions (X1,Y1,X2,Y2,…,Xσ,Yσ) of the general periodic matrix equations ∑s=0σ−1Ai,sXi+sBi,s+∑t=0σ−1Ci,tYi+tDi,t=Ni, for i = 1,2,…,σ. Th… Show more

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Cited by 12 publications
(3 citation statements)
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“…In the past, model-based optimization theory has been widely used in scientific research [2,3]. However, traditional machine learning methods are unable to determine the complex linear relationships between the renewable energy generation data, such as support vector regression (SVR) [4].…”
Section: Introductionmentioning
confidence: 99%
“…In the past, model-based optimization theory has been widely used in scientific research [2,3]. However, traditional machine learning methods are unable to determine the complex linear relationships between the renewable energy generation data, such as support vector regression (SVR) [4].…”
Section: Introductionmentioning
confidence: 99%
“…Hajarian [32] gave the matrix form of the biconjugate residual algorithm for studying the generalized reflexive and anti-reflexive solutions of a generalized Sylvester matrix equation. Then, Hajarian [33] derived four efficient iterative methods for obtaining the reflexive periodic solutions of general periodic matrix equations. Additionally, Hajarian [34] presented a conjugate gradient-like method for solving a general tensor equation with respect to the Einstein product.…”
Section: Introductionmentioning
confidence: 99%
“…In ref. [6], the reflexive periodic solutions of a class of periodic matrix equations were found based on the normal error of conjugate gradient, the normal residue of conjugate gradient and the least squares QR decomposition algorithm. Periodic Sylvester matrix equations and some types of periodic coupled matrix equations were respectively investigated in refs.…”
Section: Introductionmentioning
confidence: 99%