Krylov子空间投影法研究进展

Ｋｒｙｌｏｖ子空间投影法是一类非常有效的大型稀疏线性代数方程组解法，已被广泛应用于各种领域，随着左右空间Ｌｍ，Ｋｍ的不同取法可以得到许多人们熟知的方法．本文按矩阵Ｈｍ的不同类型，即为上Ｈｅｓｓｅｎｂｅｒｙ阵还是三对角阵将Ｋｒｙｌｏｖ子空间投影法分成两大类，从每步迭代是否具有最优性和方法的存储量、计算量等方面对Ｋｒｙｌｏｖ子空间法及其最新进展进行评述，指出Ｋｒｙｌｏｖ子空间法的局限及今后的研究方向．

Krylov Subspace Methods for Solving Large Linear Systems

Krylov subspace projection methods are known to be highly efficient, and have been widely used. Lots of well-known methods can be deduced by different selections of the left or right subspace. According to the different forms of matrix Hm, the Krylov subspace methods are classified into two groups. The storage and operations per iteration, the performance in applications and the newly advances on the methods are summarized and reviewed. Finally, several problems which need to be further investigated are also presented.