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The architecture of this set of codes and the interaction among them is shown in Figure 1.
The main testing code main code.m calls the code riemann grad unit opt.m that performs
Riemannian optimization under unitary matrix constraint. Steepest De
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预处理的共轭梯度算法和最速下降法MATLAB算法及源程序.-Preconditioning conjugate gradient algorithm and the steepest descent method MATLAB algorithms and source code.
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为精确求解散射问题,采用混合场积分方程(CFIE)、多层快速多极子算法(MLFMA)和共轭梯度算法(CG)的收敛技术。基于传统多层快速多级子算法,详细研究了二维拉格朗日插值节点数对计算精度的影响,并改进了插值方法,在不同的层采用不同的插值节点数 提出了在不同的层采用不同的精度控制来计算多级子模式数 分析了稀疏矩阵的对称性对内存使用的影响以及磁场积分方程对迭代初始值的选择。数值计算结果表明以上改进可较大幅度地提高计算精度和计算效率,同时降低内存使用,可满足复杂目标电磁散射计算要求。-Precise
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mpi多线程运用最速下降法求共轭梯度,16个线程,最多循环1000次。-mpi multi-threaded application steepest descent method the conjugate gradient, 16 threads, up to 1000 cycles.
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里面含有三种算法,包括共轭梯度矩阵求解,幂方法求本征值,同伦算法-Which contains three algorithms, including Conjugate Gradient matrix solver, power method uated the intrinsic value, homotopy method
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This paper suggests that a simple modification to the initial search direction can also substantially improve the training efficiency of almost all major optimization methods. It was discovered that if the initial search direction is locally modified
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