Newton 迭代

发布于:2025-05-16 ⋅ 阅读:(8) ⋅ 点赞:(0)

Newton 迭代

N e w t o n Newton Newton法基本格式

设给定 f ( x ) = 0 f(x)=0 f(x)=0的求根问题,我们构造以下迭代格式:
A
x k + 1 = x k − f ( x k ) f ′ ( x k ) x_{k+1}=x_k-\frac{f(x_k)}{f^{\prime}(x_k)} xk+1=xkf(xk)f(xk)

迭代函数为

φ ( x ) = x − f ( x ) f ′ ( x ) \varphi (x)=x-\frac{f(x)}{f^{\prime }(x)} φ(x)=xf(x)f(x)

其中容易得到收敛阶
lim ⁡ k → ∞ x k + 1 − x ∗ ( x k − 1 − x ∗ ) 2 = f ′ ′ ( x ∗ ) 2 f ′ ( x ∗ ) \lim_{k\rightarrow \infty}\frac{x^{k+1}-x^*}{(x_{k-1}-x^*)^2}=\frac {f^{\prime\prime}(x^*)}{2f^{\prime}(x^*)} klim(xk1x)2xk+1x=2f(x)f′′(x)

N e w t o n Newton Newton求根公式收敛的充分条件

函数 f ( x ) f(x) f(x)在区间 [ a , b ] [a,b] [a,b]上二阶光滑,且在区间 [ a , b ] [a,b] [a,b]上单调, ∣ f ′ ′ ( x ) ∣ ≤ M |f^{\prime \prime}(x)|\leq M f′′(x)M,对于选取的初解 x 0 ∈ [ a , b ] x_0 \in [a,b] x0[a,b]满足:

∣ x 0 − x ∗ ∣ ≤ 2 ∣ f ′ ( x ∗ ) ∣ M |x_0-x^*|\leq \frac{2|f^{\prime}(x^*)|}{M} x0xM2∣f(x)
其中 x ∗ x^* x f ( x ) = 0 f(x)=0 f(x)=0的根,则牛顿迭代收敛且至少为二阶。

其它相近迭代格式

简化牛顿法

x k + 1 = x k − f ( x k ) f ′ ( x 0 ) x_{k+1}=x_k-\frac{f(x_k)}{f^{\prime}(x_0)} xk+1=xkf(x0)f(xk)

牛顿下山法

λ \lambda λ 1 2 n \frac{1}{2^n} 2n1:

x ‾ k + 1 = x k − f ( x k ) f ′ ( x k ) \overline{x}_{k+1}=x_k -\frac{f(x_k)}{f^{\prime}(x_k)} xk+1=xkf(xk)f(xk)

x k + 1 = ( 1 − λ ) x k + λ x ‾ k + 1 x_{k+1}=(1-\lambda) x_k+\lambda \overline{x}_{k+1} xk+1=(1λ)xk+λxk+1

重根情形

x k + 1 = x k − m f ( x k ) f ′ ( x k ) x_{k+1}=x_k-m\frac{f(x_k)}{f^{\prime}(x_k)} xk+1=xkmf(xk)f(xk)

弦截法

使用向后均差代替导数

x k + 1 = x k − f ( x k ) f ( x k ) − f ( x k + 1 ) ( x k − x k + 1 ) x_{k+1}=x_{k}-\frac{f(x_k)}{f(x_k)-f(x_{k+1})}(x_k-x_{k+1}) xk+1=xkf(xk)f(xk+1)f(xk)(xkxk+1)


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