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复习笔记Day117:exp(A)的一种计算方法

2023-03-15 01:23 作者:间宫_卓司  | 我要投稿

这几天帮一个物理专业的网友解决了一个简单的数学问题,我觉得还蛮有意思的,就写上来了,他的原始问题是:方程%5Cexp%20%5Cleft(%20X%20%5Cright)%20%3DA的解,在不考虑辐角的情况下是否唯一,其中A2阶矩阵,X是要求解的矩阵。这里的不考虑辐角可以认为是X的特征值的虚部属于(-%5Cpi%2C%5Cpi%5D

我把原始问题稍微修改了一下,改成了如下问题,大家在看解答之前可以先自己试着做一下


117.1假设A的极小多项式为%5Cphi%20%5Cleft(%20%5Clambda%20%5Cright)%20%3D%5Cleft(%20%5Clambda%20-%5Clambda%20_1%20%5Cright)%20%5E%7Bn_1%7D%5Cleft(%20%5Clambda%20-%5Clambda%20_2%20%5Cright)%20%5E%7Bn_2%7D%5Ccdots%20%5Cleft(%20%5Clambda%20-%5Clambda%20_k%20%5Cright)%20%5E%7Bn_k%7D

解答以下问题

(1)多项式p(x)%2Cq(x)满足

p%5E%7B%5Cleft(%20j%20%5Cright)%7D%5Cleft(%20%5Clambda%20_i%20%5Cright)%20%3Dq%5E%7B%5Cleft(%20j%20%5Cright)%7D%5Cleft(%20%5Clambda%20_i%20%5Cright)%20%2Ci%3D1%2C2%2C%5Ccdots%20%2Ck%2Cj%3D0%2C1%2C%5Ccdots%20n_i-1

等价于p(A)%3Dq(A)

(2)设A是二阶矩阵,求解方程%5Cexp%20%5Cleft(%20X%20%5Cright)%20%3DA


(1)设P%5E%7B-1%7DAP%3DJ_A,其中JA的若当标准型,那么属于特征值%5Clambda_i的若当块中,大小最大的为n_i,而P%5E%7B-1%7Dp%5Cleft(%20A%20%5Cright)%20P%3Dp%5Cleft(%20P%5E%7B-1%7DAP%20%5Cright)%20%3Dp%5Cleft(%20J_A%20%5Cright)%20,现在对每一块若当块J,来计算p(J),考虑p(x)x%3D%5Clambda处的泰勒展开

p%5Cleft(%20x%20%5Cright)%20%3Dp%5Cleft(%20%5Clambda%20%5Cright)%20%2Bp'%5Cleft(%20%5Clambda%20%5Cright)%20%5Cleft(%20x-%5Clambda%20%5Cright)%20%2B%5Ccdots%20%2B%5Cfrac%7Bp%5E%7B%5Cleft(%20n%20%5Cright)%7D%5Cleft(%20%5Clambda%20%5Cright)%7D%7Bn!%7D%5Cleft(%20x-%5Clambda%20%5Cright)%20%5En

其中%5ClambdaJ的特征值,带入可得

p%5Cleft(%20J%20%5Cright)%20%3D%5Cleft%5B%20%5Cbegin%7Bmatrix%7D%0A%09p%5Cleft(%20%5Clambda%20%5Cright)%26%09%09p'%5Cleft(%20%5Clambda%20%5Cright)%26%09%09%5Ccdots%26%09%09%5Ccdots%26%09%09%5Cfrac%7Bp%5E%7B%5Cleft(%20n%20%5Cright)%7D%5Cleft(%20%5Clambda%20%5Cright)%7D%7Bn!%7D%5C%5C%0A%09%26%09%09p%5Cleft(%20%5Clambda%20%5Cright)%26%09%09p'%5Cleft(%20%5Clambda%20%5Cright)%26%09%09%5Ccdots%26%09%09%5Cvdots%5C%5C%0A%09%26%09%09%26%09%09%5Cddots%26%09%09%5Cddots%26%09%09%5Cvdots%5C%5C%0A%09%26%09%09%26%09%09%26%09%09%5Cddots%26%09%09p'%5Cleft(%20%5Clambda%20%5Cright)%5C%5C%0A%09%26%09%09%26%09%09%26%09%09%26%09%09p%5Cleft(%20%5Clambda%20%5Cright)%5C%5C%0A%5Cend%7Bmatrix%7D%20%5Cright%5D%20%3Dq(J)

从而p(A)%3Dq(A)

(2)从第一问的证明中不难得到,要找到一个多项式p(A)满足p(A)%3D%5Cexp(A),只需要

p%5E%7B%5Cleft(%20j%20%5Cright)%7D%5Cleft(%20%5Clambda%20_i%20%5Cright)%20%3D%5Cexp%5E%7B%5Cleft(%20j%20%5Cright)%7D%5Cleft(%20%5Clambda%20_i%20%5Cright)%20%2Ci%3D1%2C2%2C%5Ccdots%20%2Ck%2Cj%3D0%2C1%2C%5Ccdots%20n_i-1

就好了,这实际上就是一个赫米特插值问题,而赫米特插值问题是适定的,也就是说赫米特插值的解是存在唯一的,接下来设A有两个特征值%5Clambda_1%2C%5Clambda_2(可以相同),那么根据A的情况,计算可得如下结果

1.若A有两个相同的特征值%5Clambda_1%3D%5Clambda_2%3D%5Clambda,且A可对角化,此时X也有两个相同的特征值%5Cln%5Clambda,且X可对角化,此时X%3D%5Cleft%5B%20%5Cbegin%7Bmatrix%7D%0A%09%5Cln%20%5Clambda%26%09%09%5C%5C%0A%09%26%09%09%5Cln%20%5Clambda%5C%5C%0A%5Cend%7Bmatrix%7D%20%5Cright%5D%20

2.若A有两个不同的特征值%5Clambda_1%2C%5Clambda_2,则X也有两个不同的特征值%5Cln%20%5Clambda%20_1%2C%5Cln%20%5Clambda%20_2,通过赫米特插值可以解得

X%3D%5Cfrac%7B%5Cln%20%5Clambda%20_1-%5Cln%20%5Clambda%20_2%7D%7B%5Clambda%20_1-%5Clambda%20_2%7D%5Cleft(%20A-%5Cfrac%7B%5Clambda%20_2%5Cln%20%5Clambda%20_1-%5Clambda%20_1%5Cln%20%5Clambda%20_2%7D%7B%5Cln%20%5Clambda%20_1-%5Cln%20%5Clambda%20_2%7DI%20%5Cright)%20

3.若A有两个相同的特征值%5Clambda_1%3D%5Clambda_2%3D%5Clambda,则X也有两个不同的特征值%5Cln%20%5Clambda%20,通过赫米特插值可以解得

%5Cbegin%7Bequation%7D%0AX%3D%5Cfrac%7B1%7D%7B%5Clambda%7D(A-(%5Clambda-%5Clambda%20%5Cln%20%5Clambda)%20I)%0A%5Cend%7Bequation%7D


至于标题里提到的计算%5Cexp(A)(其实也可以计算其他矩阵函数,只要它是收敛的就好了)的方法,其实就是把矩阵的极小多项式求出来后(这通常比求若当标准型,然后再把对应的P求出来要简单吧),然后再做赫米特插值



明天应该就能看完数理统计部分了,不过比较繁琐的知识都被我跳过了,里面的思想其实是比较简单的


这个问题我竟然想了这么久,一开始我甚至还试图找到反例···我真的是数学系的学生吗?

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