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復(fù)習(xí)筆記Day117:exp(A)的一種計算方法

2023-03-15 01:23 作者:間宮_卓司  | 我要投稿

這幾天幫一個物理專業(yè)的網(wǎng)友解決了一個簡單的數(shù)學(xué)問題,我覺得還蠻有意思的,就寫上來了,他的原始問題是:方程%5Cexp%20%5Cleft(%20X%20%5Cright)%20%3DA的解,在不考慮輻角的情況下是否唯一,其中A2階矩陣,X是要求解的矩陣。這里的不考慮輻角可以認為是X的特征值的虛部屬于(-%5Cpi%2C%5Cpi%5D

我把原始問題稍微修改了一下,改成了如下問題,大家在看解答之前可以先自己試著做一下


117.1假設(shè)A的極小多項式為%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

解答以下問題

(1)多項式p(x)%2Cq(x)滿足

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

等價于p(A)%3Dq(A)

(2)設(shè)A是二階矩陣,求解方程%5Cexp%20%5Cleft(%20X%20%5Cright)%20%3DA


(1)設(shè)P%5E%7B-1%7DAP%3DJ_A,其中JA的若當標準型,那么屬于特征值%5Clambda_i的若當塊中,大小最大的為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,現(xiàn)在對每一塊若當塊J,來計算p(J),考慮p(x)x%3D%5Clambda處的泰勒展開

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,帶入可得

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)

從而p(A)%3Dq(A)

(2)從第一問的證明中不難得到,要找到一個多項式p(A)滿足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,這實際上就是一個赫米特插值問題,而赫米特插值問題是適定的,也就是說赫米特插值的解是存在唯一的,接下來設(shè)A有兩個特征值%5Clambda_1%2C%5Clambda_2(可以相同),那么根據(jù)A的情況,計算可得如下結(jié)果

1.若A有兩個相同的特征值%5Clambda_1%3D%5Clambda_2%3D%5Clambda,且A可對角化,此時X也有兩個相同的特征值%5Cln%5Clambda,且X可對角化,此時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有兩個不同的特征值%5Clambda_1%2C%5Clambda_2,則X也有兩個不同的特征值%5Cln%20%5Clambda%20_1%2C%5Cln%20%5Clambda%20_2,通過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有兩個相同的特征值%5Clambda_1%3D%5Clambda_2%3D%5Clambda,則X也有兩個不同的特征值%5Cln%20%5Clambda%20,通過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


至于標題里提到的計算%5Cexp(A)(其實也可以計算其他矩陣函數(shù),只要它是收斂的就好了)的方法,其實就是把矩陣的極小多項式求出來后(這通常比求若當標準型,然后再把對應(yīng)的P求出來要簡單吧),然后再做赫米特插值



明天應(yīng)該就能看完數(shù)理統(tǒng)計部分了,不過比較繁瑣的知識都被我跳過了,里面的思想其實是比較簡單的


這個問題我竟然想了這么久,一開始我甚至還試圖找到反例···我真的是數(shù)學(xué)系的學(xué)生嗎?

復(fù)習(xí)筆記Day117:exp(A)的一種計算方法的評論 (共 條)

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