A new parallel generic approximate sparse pseudoinverse matrix technique using a decoupled column-wise approach, based on modified row-threshold incomplete QR factorization techniques, is proposed. The explicit preconditioned conjugate gradient least squares method in conjunction with the new parallel generic approximate sparse pseudoinverse matrix technique is used for solving linear least square problems. Numerical results indicating the applicability and effectiveness of the proposed parallel generic approximate sparse pseudoinverse matrix techniques for solving various model problems are given.

中文翻译：

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关于求解线性最小二乘问题的并行近似伪逆矩阵技术的注记

提出了一种基于改进的行阈值不完全QR分解技术的，基于列解耦的并行通用近似稀疏伪逆矩阵技术。显式的预处理共轭梯度最小二乘法与新的并行通用近似稀疏伪逆矩阵技术相结合，用于解决线性最小二乘问题。数值结果表明了所提出的并行通用近似稀疏伪逆矩阵技术在解决各种模型问题中的适用性和有效性。