Re: 是變分法嗎?
※ 引述《physmd (smd)》之銘言:
: 我變分法是很多年前學的,而且只懂皮毛......
: 底下這個問題不好意思我用英文輸入啦 :P
: 有請版友指點,多謝~~
: Consider real valued functions in the closed domain [0, 1]
: Find f(x) that minimizes: Integrate{ g(x)^2 / f(x) },
: with respect to a given g(x), integrate over x from 0 to 1,
: subject to the constraints
: (1) f > 0 for all x in [0, 1]
: (2) |f| = 1, that is, Integrate{ f(x) } over x = 0 to 1 is unity.
: Suppose everything you need to know about g(x) is completely specified.
: (the derivative or anti-derivative of g(x) etc)
: In general g(x) can be just some real valued integrable function (that doesn't
: even have to be piece-wise continuous), but if needed we can focus on the solution
: f(x) for some smooth g(x).
: p.s.
: Some of you might notice that f is a probability density.
: In fact, this question is simplified from a question regarding minimizing
: the variance of some stuff.
是變分沒錯, 不要太要求嚴謹, 就像下面這樣做.
Let f(x) be a function which satisfies (1), (2) and minimizes
Int{ g(x)^2 / f(x) }. Let h(x) be any smooth function satisfying
Int{ h(x) }=0. Then f(x)+εh(x) also satisfies (1) and (2)
when ε is very close to zero.
Therefore, the function I(ε) := Int{ g(x)^2 / (f(x)+εh(x)) } has a
local maximum at ε=0, which implies I'(0)=0.
By direct computation, we find this means
Int{ [g(x)^2/f(x)^2].h(x) } = 0.
Note that this is true for arbitrary smooth function h(x)
satisfying Int{h(x)}=0. The remaining problem is to ask what f(x) makes
this possible.
By observation, we find it's true when
g(x)^2/f(x)^2 is a constant. Hence f(x)=c|g(x)|,
where c is the constant so that (2) holds.
Precisely, c = 1/Int{|g(x)|}.
--
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※ 編輯: llrabel 來自: 140.109.105.70 (01/15 15:16)
※ 編輯: llrabel 來自: 140.109.105.70 (01/15 15:17)
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