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中文摘要：
提出一类新的曲线搜索下的多步下降算法，在较弱条件下证明了算法具有全局收敛性和线性收敛速率．算法利用前面多步迭代点的信息和曲线搜索技巧产生新的迭代点，收敛稳定，不用计算和存储矩阵，适于求解大规模优化问题．数值试验表明算法是有效的．
英文摘要：
This paper presents a new class of multi-step descent methods with curve search rule. We prove its global convergence and linear convergence rate under some mild conditions. The methods use to generate new iterative poin and be more suitable to solve and storage of some matrices. pr ts evious multi-step iterative information and curve search rule at each iteration. This makes the new method converge stably large scale optimization problems by avoiding the computation Numerical experiments show that the new method is available and efficient in practical computation.
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Positive periodic solutions for a nonautonomous delayed predator-prey system with diffusion and impu
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