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幾類特殊遞推數(shù)列的矩陣算法(下篇)

2023-08-14 12:20 作者:現(xiàn)代微積分  | 我要投稿

前言

又“拋棄”了b站幾天,再次回來更這擱置的下篇。

這次我們要談的是一階分式遞推。

在此之前,我們要講講一階分式函數(shù)y%3D%5Cfrac%7B%5Ctext%7B~%7Dx%2B%5Ctext%7B~%7D%7D%7B%5Ctext%7B~%7Dx%2B%5Ctext%7B~%7D%7D%20(~表系數(shù))的復(fù)合運算


f(x)%3D%5Cfrac%7Ba_1x%2Ba_2%7D%7Ba_3x%2Ba_4%7D%20g(x)%3D%5Cfrac%7Ba_5x%2Ba_6%7D%7Ba_7x%2Ba_8%7D%20

則有:

%5Cbegin%7Balign%7D%20g(f(x))%26%3D%5Cfrac%7Ba_5(%5Cfrac%7Ba_1x%2Ba_2%7D%7Ba_3x%2Ba_4%7D%20)%2Ba_6%7D%7Ba_7(%5Cfrac%7Ba_1x%2Ba_2%7D%7Ba_3x%2Ba_4%7D%20)%2Ba_8%7D%20%5C%5C%20%26%3D%5Cfrac%7Ba_5(a_1x%2Ba_2)%2Ba_6(a_3x%2Ba_4)%7D%7Ba_7(a_1x%2Ba_2)%2Ba_8(a_3x%2Ba_4)%7D%20%5C%5C%20%26%3D%5Cfrac%7B(a_1a_5%2Ba_3a_6)x%2B(a_2a_5%2Ba_4a_6)%7D%7B(a_1a_7%2Ba_3a_8)x%2B(a_2a_7%2Ba_4a_8)%7D%20%20%5Cend%7Balign%7D

誒?我們看這系數(shù)的變化,這跟矩陣的乘法非常類似耶!

記矩陣F%3D%5Cbegin%7Bbmatrix%7D%20%20a_1%20%26a_2%20%5C%5C%20%20a_3%20%26a_4%20%5Cend%7Bbmatrix%7D,G%3D%5Cbegin%7Bbmatrix%7D%20%20a_5%20%26a_6%20%5C%5C%20%20a_7%20%26a_8%20%5Cend%7Bbmatrix%7D

G%5Ccdot%20F%3D%20%5Cbegin%7Bbmatrix%7D%20a_1a_5%2Ba_3a_6%20%20%26a_2a_5%2Ba_4a_6%20%5C%5C%20a_1a_7%2Ba_3a_8%20%20%26a_2a_7%2Ba_4a_8%20%5Cend%7Bbmatrix%7D


因此,要算一次分式的復(fù)合運算,可以等價為計算其系數(shù)矩陣的乘積

即將f(x)%3D%5Cfrac%7Ba_1x%2Ba_2%7D%7Ba_3x%2Ba_4%7D%20類比為%5Cbegin%7Bbmatrix%7D%0A%20f(x)%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%3D%5Cbegin%7Bbmatrix%7D%0Aa_1%20%26a_2%20%5C%5C%0Aa_3%20%26a_4%0A%5Cend%7Bbmatrix%7D%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0Ax%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D

ps:注意這里是“類比”而不是相等,右邊矩陣算出的是第1行和第2行分別對于原式中的分子和分母

這是極大的一步突破!目前個人認(rèn)知有限只通過上述暴算證明了其可類比性,或許有更底層的邏輯尚未挖掘,留予后續(xù)思考[滑稽]

舉個例子練練手:

已知f(x)%3D%5Cfrac%7Bx%2B1%7D%7B2x%2B3%7D%2Cg(x)%3D%5Cfrac%7B3x-1%7D%7Bx-2%7D%2Ch(x)%3D%5Cfrac%7B-x%2B2%7D%7Bx-3%7D%20%20%20

f(g(h(x)))

寫出上述函數(shù)對應(yīng)的系數(shù)矩陣:

F%3D%5Cbegin%7Bbmatrix%7D%20%201%20%261%20%5C%5C%20%202%20%263%20%5Cend%7Bbmatrix%7D%2C%20G%3D%5Cbegin%7Bbmatrix%7D%20%203%20%26-1%20%5C%5C%20%201%20%26-2%20%5Cend%7Bbmatrix%7D%2C%20H%3D%5Cbegin%7Bbmatrix%7D%20%20-1%20%262%20%5C%5C%20%201%20%26-3%20%5Cend%7Bbmatrix%7D

根據(jù)由里到外的順序,以此進(jìn)行矩陣乘法運算

%5Cbegin%7Balign%7D%20%26F%5Ccdot%20G%5Ccdot%20H%5C%5C%20%3D%26%20%5Cbegin%7Bbmatrix%7D%20%201%20%261%20%5C%5C%20%202%20%263%20%5Cend%7Bbmatrix%7D%20%5Ccdot%20%5Cbegin%7Bbmatrix%7D%20%203%20%26-1%20%5C%5C%20%201%20%26-2%20%5Cend%7Bbmatrix%7D%20%5Ccdot%20%5Cbegin%7Bbmatrix%7D%20%20-1%20%262%20%5C%5C%20%201%20%26-3%20%5Cend%7Bbmatrix%7D%5C%5C%20%3D%26%5Cbegin%7Bbmatrix%7D%20%201%20%261%20%5C%5C%20%202%20%263%20%5Cend%7Bbmatrix%7D%20%5Ccdot%20%5Cbegin%7Bbmatrix%7D%20%20-4%20%269%20%5C%5C%20%20-3%20%268%20%5Cend%7Bbmatrix%7D%5C%5C%20%3D%26%5Cbegin%7Bbmatrix%7D%20%20-7%20%2617%20%5C%5C%20%20-17%20%2642%20%5Cend%7Bbmatrix%7D%20%5Cend%7Balign%7D

因此f(g(h(x)))%3D%5Cfrac%7B-7x%2B17%7D%7B-17x%2B42%7D%20

有了以上鋪墊,我們就能推導(dǎo)一階分式遞推a_%7Bn%2B1%7D%3D%5Cfrac%7Bc_1a_n%2Bc_2%7D%7Bc_3a_n%2Bc_4%7D%20(c表系數(shù))

f(x)%3D%5Cfrac%7Bc_1x%2Bc_2%7D%7Bc_3x%2Bc_4%7D%20,則a_%7Bn%2B1%7D%3Df(a_n)

于是有:a_2%3Df(a_1)%2Ca_3%3Df(a_2)%3Df(f(a_1))

a_4%3Df(a_3)%3Df(f(f(a_1))),

以此類推,我們發(fā)現(xiàn),求下一項就是把上一項的值代回函數(shù)f(x)的自變量x中,要求a_n就要對函數(shù)f(x)自身復(fù)合n-1次。而f(x)是一階分式函數(shù),根據(jù)上面的推導(dǎo),我們可將復(fù)合運算等價為矩陣運算來研究。由于是自身復(fù)合,所以復(fù)合n-1次,那么矩陣就乘以n-1次方

舉個例子,已知a_1%3D1,a_%7Bn%2B1%7D%3D%5Cfrac%7B-2a_n-5%7D%7B8a_n-16%7D%20

類比為%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn%2B1%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%0A%3D%5Cbegin%7Bbmatrix%7D%0A%20-2%20%26-5%20%5C%5C%0A8%20%20%26-16%0A%5Cend%7Bbmatrix%7D%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D

于是構(gòu)成遞推

%5Cbegin%7Balign%7D%0A%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn%2B1%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%0A%26%3D%5Cbegin%7Bbmatrix%7D%0A%20-2%20%26-5%20%5C%5C%0A8%20%20%26-16%0A%5Cend%7Bbmatrix%7D%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%5C%5C%0A%26%3D%5Cbegin%7Bbmatrix%7D%0A%20-2%20%26-5%20%5C%5C%0A8%20%20%26-16%0A%5Cend%7Bbmatrix%7D%5E2%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn-1%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%5C%5C%0A%26%3D...%0A%5Cend%7Balign%7D

%3D%5Cbegin%7Bbmatrix%7D%0A%20-2%20%26-5%20%5C%5C%0A8%20%20%26-16%0A%5Cend%7Bbmatrix%7D%5E%7Bn%7D%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0Aa_%7B1%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D


我們要計算a_n,因此要作n-1次變換,即

%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%3D%5Cbegin%7Bbmatrix%7D%0A%20-2%20%26-5%20%5C%5C%0A8%20%20%26-16%0A%5Cend%7Bbmatrix%7D%5E%7Bn-1%7D%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0Aa_%7B1%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D

處理矩陣次方運算,同樣采用對角化,

%5Cbegin%7Bbmatrix%7D%0A%20-2%20%26-5%20%5C%5C%0A8%20%20%26-16%0A%5Cend%7Bbmatrix%7D%5E%7Bn-1%7D%0A%3D%0A%5Cbegin%7Bbmatrix%7D%0A%201%20%26%205%5C%5C%0A%202%20%264%0A%5Cend%7Bbmatrix%7D%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0A%20(-12)%5E%7Bn-1%7D%20%26%200%5C%5C%0A%200%20%26(-6)%5E%7Bn-1%7D%0A%5Cend%7Bbmatrix%7D%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0A%20-%5Cfrac%7B2%7D%7B3%7D%20%26%20%5Cfrac%7B5%7D%7B6%7D%20%5C%5C%0A%20%5Cfrac%7B1%7D%7B3%7D%20%26-%5Cfrac%7B1%7D%7B6%7D%20%0A%5Cend%7Bbmatrix%7D

代入化簡得:

%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%3D%0A%5Cbegin%7Bbmatrix%7D%0A%20%5Cfrac%7B1%7D%7B6%7D%5Ctimes%20(-12)%5E%7Bn-1%7D%2B%5Cfrac%7B5%7D%7B6%7D%5Ctimes%20(-6)%5E%7Bn-1%7D%20%20%5C%5C%0A%20%5Cfrac%7B1%7D%7B3%7D%5Ctimes%20(-12)%5E%7Bn-1%7D%2B%5Cfrac%7B2%7D%7B3%7D%5Ctimes%20(-6)%5E%7Bn-1%7D%20%0A%5Cend%7Bbmatrix%7D

還原分式,即:

a_n%3D%5Cfrac%7B%20%5Cfrac%7B1%7D%7B6%7D%5Ctimes%20(-12)%5E%7Bn-1%7D%2B%5Cfrac%7B5%7D%7B6%7D%5Ctimes%20(-6)%5E%7Bn-1%7D%20%7D%7B%20%5Cfrac%7B1%7D%7B3%7D%5Ctimes%20(-12)%5E%7Bn-1%7D%2B%5Cfrac%7B2%7D%7B3%7D%5Ctimes%20(-6)%5E%7Bn-1%7D%20%7D%20

稍加化簡,即得:

a_n%3D%5Cfrac%7B2%5E%7Bn-1%7D%2B5%7D%7B2%5En%2B4%7D%20

也即上下同除(-6)%5E%7Bn-1%7D%20,以及部分繁分?jǐn)?shù)化簡

有了這個背景,我們就可以證明一階分式遞推中一些神秘的周期結(jié)論了

如:已知a_%7Bn%2B1%7D%3D-%5Cfrac%7B1%7D%7B1%2Ba_n%7D%20,證明其是周期為3的數(shù)列

通過暴力迭代可以證明,而前文我們已經(jīng)鋪墊了利用矩陣將這一迭代進(jìn)行等價轉(zhuǎn)化的方法,于是我們可從更高的視角來欣賞這一變換

化為標(biāo)準(zhǔn)形式a_%7Bn%2B1%7D%3D%5Cfrac%7B-1%7D%7Ba_n%2B1%7D%20,類比為矩陣:%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn%2B1%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%0A%3D%5Cbegin%7Bbmatrix%7D%0A%20%200%26%20-1%5C%5C%0A1%20%20%261%0A%5Cend%7Bbmatrix%7D%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D

系數(shù)矩陣為:%5Cbegin%7Bbmatrix%7D%0A%20%200%26%20-1%5C%5C%0A1%20%20%261%0A%5Cend%7Bbmatrix%7D

經(jīng)計算得%5Cbegin%7Bbmatrix%7D%0A%20%200%26%20-1%5C%5C%0A1%20%20%261%0A%5Cend%7Bbmatrix%7D%5E3%3D%0A%0A%5Cbegin%7Bbmatrix%7D%0A%20-%201%26%200%5C%5C%0A0%20%20%26-1%0A%5Cend%7Bbmatrix%7D%0A%3D%0A-%5Cbegin%7Bbmatrix%7D%0A%20%201%26%200%5C%5C%0A0%20%20%261%0A%5Cend%7Bbmatrix%7D,這時化為一個非零系數(shù)乘一個單位陣的形式,于是周期T=4


為什么有個非零系數(shù)也可以呢?答案是一階分式系數(shù)的齊次性

矩陣4次方運算,即

%5Cbegin%7Balign%7D%0A%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn%2B1%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%0A%26%3D%5Cbegin%7Bbmatrix%7D%0A%20%200%26%20-1%5C%5C%0A1%20%20%261%0A%5Cend%7Bbmatrix%7D%5E4%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn-3%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%5C%5C%0A%26%3D%5Cbegin%7Bbmatrix%7D%0A%20%20-1%26%200%5C%5C%0A0%20%20%26-1%0A%5Cend%7Bbmatrix%7D%0A%5Ccdot%20%0A%5Cbegin%7Bbmatrix%7D%0Aa_%7Bn-3%7D%20%5C%5C%0A1%0A%5Cend%7Bbmatrix%7D%5C%5C%0A%5Cend%7Balign%7D

還原分式,即:a_%7Bn%2B1%7D%3D%5Cfrac%7B-1a_%7Bn-3%7D%7D%7B-1%7D%3Da_%7Bn-3%7D%20

注意這里分子分母的-1可約去,也即系數(shù)的齊次性,故單位陣前存在非零系數(shù)是允許的


我們再來看看系數(shù)矩陣%5Cbegin%7Bbmatrix%7D%0A%20%200%26%20-1%5C%5C%0A1%20%20%261%0A%5Cend%7Bbmatrix%7D的特征根:

%5Clambda%20_%7B1%2C2%7D%3D%5Cfrac%7B1%7D%7B2%7D%20%5Cpm%20%5Cfrac%7B%5Csqrt%7B3%7D%20%7D%7B2%7Di%20%3D%5Cmathrm%7Be%7D%20%5E%7B%5Cpm%20%5Cfrac%7B%5Cpi%7D%7B3%7Di%20%7D%20

于是對角化后,有:%5Cbegin%7Bbmatrix%7D%0A%20%200%26%20-1%5C%5C%0A1%20%20%261%0A%5Cend%7Bbmatrix%7D%0A%3DS%5Ccdot%20J%5Ccdot%20S%5E%7B-1%7D

其中J%3D%5Cbegin%7Bbmatrix%7D%0A%5Cmathrm%7Be%7D%20%5E%7B%5Cfrac%7B%5Cpi%7D%7B3%7Di%20%7D%20%20%260%20%5C%5C%0A0%20%20%26%5Cmathrm%7Be%7D%20%5E%7B-%5Cfrac%7B%5Cpi%7D%7B3%7Di%20%7D%0A%5Cend%7Bbmatrix%7D

于是有J%5E3%3D%5Cbegin%7Bbmatrix%7D%0A-1%20%20%260%20%5C%5C%0A%20%200%26-1%0A%5Cend%7Bbmatrix%7D%0A%3D-%5Cbegin%7Bbmatrix%7D%0A%201%20%26%200%5C%5C%0A0%20%20%261%0A%5Cend%7Bbmatrix%7D

因此周期為3。而這,竟也是特殊輻角的旋轉(zhuǎn)周期性造成的!也即從實軸開始以每次%5Cfrac%7B%5Cpi%7D%7B3%7D%20的單位轉(zhuǎn)動,轉(zhuǎn)3次恰好回到實軸

再如:

已知a_%7Bn%2B1%7D%3D1-%5Cfrac%7B1%7D%7Ba_n%7D%20,證明其是周期為3的數(shù)列

同理,化為標(biāo)準(zhǔn)形式a_%7Bn%2B1%7D%3D%5Cfrac%7Ba_n-1%7D%7Ba_n%7D%20

系數(shù)矩陣:%5Cbegin%7Bbmatrix%7D%0A%201%20%26-1%20%5C%5C%0A1%20%20%260%0A%5Cend%7Bbmatrix%7D

有:%5Cbegin%7Bbmatrix%7D%0A%201%20%26-1%20%5C%5C%0A1%20%20%260%0A%5Cend%7Bbmatrix%7D%5E3%3D%0A-%5Cbegin%7Bbmatrix%7D%0A%201%20%26%200%5C%5C%0A%200%20%261%0A%5Cend%7Bbmatrix%7D

于是周期為3


系數(shù)矩陣特征根為:%5Clambda%20_%7B1%2C2%7D%3D%5Cfrac%7B1%7D%7B2%7D%20%5Cpm%20%5Cfrac%7B%5Csqrt%7B3%7D%20%7D%7B2%7Di%20%3D%5Cmathrm%7Be%7D%20%5E%7B%5Cpm%20%5Cfrac%7B%5Cpi%7D%7B3%7Di%20%7D%20

因此也是旋轉(zhuǎn)3次后回到實軸,與前例道理相同


同樣,對角化的處理也在系數(shù)矩陣可對角化時使用,因此也還存在沒有解決的情況,也即特征根為重根的情況,也先遺留于此后續(xù)再解決。

數(shù)學(xué)知識,是多么的美妙兼強大!許多云里霧里的“套路”也好,證明超出高中范圍的“定理”也罷,我愿通過后續(xù)的學(xué)習(xí)與鉆研,把先前的“迷霧”驅(qū)散,沖破應(yīng)試的罩子去探尋數(shù)學(xué)那一份真實而優(yōu)雅的美!

哈哈哈哈,我還是依舊的中二,盡量別活成自己討厭的樣子~(





幾類特殊遞推數(shù)列的矩陣算法(下篇)的評論 (共 條)

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