method of iteration

There establish Kantorovich-type theorem for this kind of method by using majorizing function,and give an almost sharper error estimate than Newton method.

从求解非线性方程f(x)=0的一维“牛顿类”迭代法出发,在Banach空间中建立了“牛顿类”迭代公式,用优函数的方法,建立了相应的Kantorovich定理,并给出了比牛顿迭代更好的误差估计。

Under one global condition on the function, instead of two, the convergence determinations are established by using quadratic and cubical majorizing functions respectively.

进一步，我们利用三次优函数技巧建立了在某种意义“更优”的收敛性准则。

Some improving schemes are brought out based on discussing the chaos algorithm, and are simulated by usual optimizing function.

本文通过在对一种混沌算法进行讨论的基础上,提出一些改进措施,并利用常用寻优函数进行仿真验证。

We derived one iterative method for solving nonlinear equations,proved the properities of the majoring function and the convergence of the majoring sequence, gave one variety of iterative method and proved it.

提出了一种避免King Werner迭代格式导映射求逆的迭代算法,并利用优函数证明了其在统一判定条件下的收敛性。

We derived one iterative methed for solving polynomial equation, proved the properities of the majoring function and the convergence of the majoring sequence, gave one variety of iterative method and proved it.

本文推导出切比雪夫迭代应用于多项式求根的迭代形式 ,阐述了优函数的一些性质以及优序列的收敛性 ,给出了切比雪夫迭代应用于多项式求根的变形形式并证明了收敛性定

2) The convergence of applying iteration by taking the advantage of majoring function.

首先指出切比雪夫迭代应用于多项式求根与一解多项式方程的并行迭代的等价性 ,并利用优函数来证明迭代的收敛性 ,给出 β的大致取值范

In this paper, a new convergence theorem and error estimates for two types of generalized method are obtained by means of cubic major function, under the unified determination.

该文在统一判定条件下 ,借助于三次优函数 ,给出了两类一般迭代法的不同于以前的收敛性和误差估

The optimal function equation is established.

求导建立最优函数方程,将两种极限状态参数代入最优函数方程,获得一个关于阻尼比的超越方程,用数值解法确定最优阻尼比。