‚åŁÎ“·„´Šš‡ðŠp‡¢‡½‹âfi`fiI…A…‰…S…−…Y…•‡ÌMarkovŸA“½fiI›ð’Í

Similar documents
Ł\”ƒ-2005

第90回日本感染症学会学術講演会抄録(I)

本文/目次(裏白)

1 1.1 ( ). z = a + bi, a, b R 0 a, b 0 a 2 + b 2 0 z = a + bi = ( ) a 2 + b 2 a a 2 + b + b 2 a 2 + b i 2 r = a 2 + b 2 θ cos θ = a a 2 + b 2, sin θ =

2 1 κ c(t) = (x(t), y(t)) ( ) det(c (t), c x (t)) = det (t) x (t) y (t) y = x (t)y (t) x (t)y (t), (t) c (t) = (x (t)) 2 + (y (t)) 2. c (t) =

I A A441 : April 15, 2013 Version : 1.1 I Kawahira, Tomoki TA (Shigehiro, Yoshida )

II A A441 : October 02, 2014 Version : Kawahira, Tomoki TA (Kondo, Hirotaka )

³ÎΨÏÀ

日本内科学会雑誌第98巻第4号

日本内科学会雑誌第97巻第7号

抄録/抄録1    (1)V

tnbp59-21_Web:P2/ky132379509610002944

y = x x R = 0. 9, R = σ $ = y x w = x y x x w = x y α ε = + β + x x x y α ε = + β + γ x + x x x x' = / x y' = y/ x y' =

パーキンソン病治療ガイドライン2002

研修コーナー

TOP URL 1

meiji_resume_1.PDF

201711grade1ouyou.pdf

III 1 (X, d) d U d X (X, d). 1. (X, d).. (i) d(x, y) d(z, y) d(x, z) (ii) d(x, y) d(z, w) d(x, z) + d(y, w) 2. (X, d). F X.. (1), X F, (2) F 1, F 2 F


微分積分 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 初版 1 刷発行時のものです.


N cos s s cos ψ e e e e 3 3 e e 3 e 3 e

I

6.1 (P (P (P (P (P (P (, P (, P.

ii 3.,. 4. F. (), ,,. 8.,. 1. (75%) (25%) =7 20, =7 21 (. ). 1.,, (). 3.,. 1. ().,.,.,.,.,. () (12 )., (), 0. 2., 1., 0,.

量子力学 問題

D = [a, b] [c, d] D ij P ij (ξ ij, η ij ) f S(f,, {P ij }) S(f,, {P ij }) = = k m i=1 j=1 m n f(ξ ij, η ij )(x i x i 1 )(y j y j 1 ) = i=1 j

医系の統計入門第 2 版 サンプルページ この本の定価 判型などは, 以下の URL からご覧いただけます. このサンプルページの内容は, 第 2 版 1 刷発行時のものです.



9 2 1 f(x, y) = xy sin x cos y x y cos y y x sin x d (x, y) = y cos y (x sin x) = y cos y(sin x + x cos x) x dx d (x, y) = x sin x (y cos y) = x sin x

No δs δs = r + δr r = δr (3) δs δs = r r = δr + u(r + δr, t) u(r, t) (4) δr = (δx, δy, δz) u i (r + δr, t) u i (r, t) = u i x j δx j (5) δs 2

6.1 (P (P (P (P (P (P (, P (, P.101

newmain.dvi


2 G(k) e ikx = (ik) n x n n! n=0 (k ) ( ) X n = ( i) n n k n G(k) k=0 F (k) ln G(k) = ln e ikx n κ n F (k) = F (k) (ik) n n= n! κ n κ n = ( i) n n k n

Untitled

A 2 3. m S m = {x R m+1 x = 1} U + k = {x S m x k > 0}, U k = {x S m x k < 0}, ϕ ± k (x) = (x 0,..., ˆx k,... x m ) 1. {(U ± k, ϕ± k ) 0 k m} S m 1.2.

gr09.dvi

1 1.1 [ ]., D R m, f : D R n C -. f p D (df) p : (df) p : R m R n f(p + vt) f(p) : v lim. t 0 t, (df) p., R m {x 1,..., x m }, (df) p (x i ) =

(Basics of Proability Theory). (Probability Spacees ad Radom Variables,, (Ω, F, P ),, X,. (Ω, F, P ) (probability space) Ω ( ω Ω ) F ( 2 Ω ) Ω σ (σ-fi


S I. dy fx x fx y fx + C 3 C vt dy fx 4 x, y dy yt gt + Ct + C dt v e kt xt v e kt + C k x v k + C C xt v k 3 r r + dr e kt S Sr πr dt d v } dt k e kt

ohpmain.dvi

I z n+1 = zn 2 + c (c ) c pd L.V. K. 2

A

数学概論I

Part () () Γ Part ,

TOP URL 1

W u = u(x, t) u tt = a 2 u xx, a > 0 (1) D := {(x, t) : 0 x l, t 0} u (0, t) = 0, u (l, t) = 0, t 0 (2)

Chapter9 9 LDPC sum-product LDPC 9.1 ( ) 9.2 c 1, c 2, {0, 1, } SUM, PROD : {0, 1, } {0, 1, } SUM(c 1, c 2,, c n ) := { c1 + + c n (c n0 (1 n

tomocci ,. :,,,, Lie,,,, Einstein, Newton. 1 M n C. s, M p. M f, p d ds f = dxµ p ds µ f p, X p = X µ µ p = dxµ ds µ p. µ, X µ.,. p,. T M p.

日本内科学会雑誌第102巻第4号

Microsoft Word - 11問題表紙(選択).docx

S I. dy fx x fx y fx + C 3 C dy fx 4 x, y dy v C xt y C v e kt k > xt yt gt [ v dt dt v e kt xt v e kt + C k x v + C C k xt v k 3 r r + dr e kt S dt d

(Basics of Proability Theory). (Probability Spacees ad Radom Variables,, (Ω, F, P ),, X,. (Ω, F, P ) (probability space) Ω ( ω Ω ) F ( 2 Ω ) Ω σ (σ-fi

,. Black-Scholes u t t, x c u 0 t, x x u t t, x c u t, x x u t t, x + σ x u t, x + rx ut, x rux, t 0 x x,,.,. Step 3, 7,,, Step 6., Step 4,. Step 5,,.

v v = v 1 v 2 v 3 (1) R = (R ij ) (2) R (R 1 ) ij = R ji (3) 3 R ij R ik = δ jk (4) i=1 δ ij Kronecker δ ij = { 1 (i = j) 0 (i

II ( ) (7/31) II ( [ (3.4)] Navier Stokes [ (6/29)] Navier Stokes 3 [ (6/19)] Re

LLG-R8.Nisus.pdf

nsg04-28/ky208684356100043077

x () g(x) = f(t) dt f(x), F (x) 3x () g(x) g (x) f(x), F (x) (3) h(x) = x 3x tf(t) dt.9 = {(x, y) ; x, y, x + y } f(x, y) = xy( x y). h (x) f(x), F (x

ii 3.,. 4. F. ( ), ,,. 8.,. 1. (75% ) (25% ) =7 24, =7 25, =7 26 (. ). 1.,, ( ). 3.,...,.,.,.,.,. ( ) (1 2 )., ( ), 0., 1., 0,.


O1-1 O1-2 O1-3 O1-4 O1-5 O1-6

1 I

all.dvi

9. 05 L x P(x) P(0) P(x) u(x) u(x) (0 < = x < = L) P(x) E(x) A(x) P(L) f ( d EA du ) = 0 (9.) dx dx u(0) = 0 (9.2) E(L)A(L) du (L) = f (9.3) dx (9.) P

ax 2 + bx + c = n 8 (n ) a n x n + a n 1 x n a 1 x + a 0 = 0 ( a n, a n 1,, a 1, a 0 a n 0) n n ( ) ( ) ax 3 + bx 2 + cx + d = 0 4

(3) (2),,. ( 20) ( s200103) 0.7 x C,, x 2 + y 2 + ax = 0 a.. D,. D, y C, C (x, y) (y 0) C m. (2) D y = y(x) (x ± y 0), (x, y) D, m, m = 1., D. (x 2 y

第86回日本感染症学会総会学術集会後抄録(I)

( )/2 hara/lectures/lectures-j.html 2, {H} {T } S = {H, T } {(H, H), (H, T )} {(H, T ), (T, T )} {(H, H), (T, T )} {1

1 (1) () (3) I 0 3 I I d θ = L () dt θ L L θ I d θ = L = κθ (3) dt κ T I T = π κ (4) T I κ κ κ L l a θ L r δr δl L θ ϕ ϕ = rθ (5) l

プリント


2 2 1?? 2 1 1, 2 1, 2 1, 2, 3,... 1, 2 1, 3? , 2 2, 3? k, l m, n k, l m, n kn > ml...? 2 m, n n m

f(x) = f(x ) + α(x)(x x ) α(x) x = x. x = f (y), x = f (y ) y = f f (y) = f f (y ) + α(f (y))(f (y) f (y )) f (y) = f (y ) + α(f (y)) (y y ) ( (2) ) f

ii 3.,. 4. F. (), ,,. 8.,. 1. (75% ) (25% ) =9 7, =9 8 (. ). 1.,, (). 3.,. 1. ( ).,.,.,.,.,. ( ) (1 2 )., ( ), 0. 2., 1., 0,.

.2 ρ dv dt = ρk grad p + 3 η grad (divv) + η 2 v.3 divh = 0, rote + c H t = 0 dive = ρ, H = 0, E = ρ, roth c E t = c ρv E + H c t = 0 H c E t = c ρv T

: , 2.0, 3.0, 2.0, (%) ( 2.

* n x 11,, x 1n N(µ 1, σ 2 ) x 21,, x 2n N(µ 2, σ 2 ) H 0 µ 1 = µ 2 (= µ ) H 1 µ 1 µ 2 H 0, H 1 *2 σ 2 σ 2 0, σ 2 1 *1 *2 H 0 H

放射線専門医認定試験(2009・20回)/HOHS‐05(基礎二次)

プログラム

v er.1/ c /(21)


simx simxdx, cosxdx, sixdx 6.3 px m m + pxfxdx = pxf x p xf xdx = pxf x p xf x + p xf xdx 7.4 a m.5 fx simxdx 8 fx fx simxdx = πb m 9 a fxdx = πa a =

Dirac 38 5 Dirac 4 4 γ µ p µ p µ + m 2 = ( p µ γ µ + m)(p ν γ ν + m) (5.1) γ = p µ p ν γ µ γ ν p µ γ µ m + mp ν γ ν + m 2 = 1 2 p µp ν {γ µ, γ ν } + m

1 (Berry,1975) 2-6 p (S πr 2 )p πr 2 p 2πRγ p p = 2γ R (2.5).1-1 : : : : ( ).2 α, β α, β () X S = X X α X β (.1) 1 2


() Remrk I = [0, ] [x i, x i ]. (x : ) f(x) = 0 (x : ) ξ i, (f) = f(ξ i )(x i x i ) = (x i x i ) = ξ i, (f) = f(ξ i )(x i x i ) = 0 (f) 0.

DVIOUT

I A A441 : April 21, 2014 Version : Kawahira, Tomoki TA (Kondo, Hirotaka ) Google

2011de.dvi

4. ϵ(ν, T ) = c 4 u(ν, T ) ϵ(ν, T ) T ν π4 Planck dx = 0 e x 1 15 U(T ) x 3 U(T ) = σt 4 Stefan-Boltzmann σ 2π5 k 4 15c 2 h 3 = W m 2 K 4 5.

Gmech08.dvi

all.dvi

SFGÇÃÉXÉyÉNÉgÉãå`.pdf

() x + y + y + x dy dx = 0 () dy + xy = x dx y + x y ( 5) ( s55906) 0.7. (). 5 (). ( 6) ( s6590) 0.8 m n. 0.9 n n A. ( 6) ( s6590) f A (λ) = det(a λi)


Transcription:

Markov 2009 10 2 Markov 2009 10 2 1 / 25

1 (GA) 2 GA 3 4 Markov 2009 10 2 2 / 25

(GA) (GA) L ( 1) I := {0, 1} L f : I (0, ) M( 2) S := I M GA (GA) f (i) i I Markov 2009 10 2 3 / 25

(GA) ρ(i, j), i, j I 2 i, j (L ) d(x, y), x, y S 2 x, y (LM ) 0 < µ < 1 M µ LM µ x, y S x M µ y : M µ [x, y] := µ d(x,y) (1 µ) LM d(x,y) > 0 Markov 2009 10 2 4 / 25

(GA) C (i 1,, i L ), (i 1,, i L ) I, π {1,, L}: i k, i k, k π x, y S x C y : C[x, y] ( ) π = {1,, k}(1 k L) = ( ) k {1,, L} 1 Markov 2009 10 2 5 / 25

(GA) x = (x 1,, x M ), y = (y 1,, y M ) S x k, y k I, k = 1,, M x y {x 1,, x M } {y 1,, y M } β > 0 S β y k g β (y k ) := f (y k ) β / M f (x k ) β (β: ) k=1 x, y S x S β y : { M S β [x, y] := k=1 g β(y k ), x y 0, x y Markov 2009 10 2 6 / 25

(GA) µ, β GA µ, β GA x, u, v, y S x Mµ u C v S β y : Q µ,β [x, y] := M µ [x, u]c[u, v]s β [v, y] u,v S f (i) i I Markov 2009 10 2 7 / 25

GA GA Q µ,β = (Q µ,β [x, y]) x,y S : Markov (X n ) S ( Markov ) 0 < µ < 1 = Q µ,β [x, y] > 0 = k s.t. Qµ,β k [x, y] > 0 ( ) x S gcd{n P(X n = x X 0 = x) > 0} 1 ( ) Markov Markov = GA Markov (0 < µ < 1) = (q µ,β (x)) x S [ qµ,β (1) q µ,β (σ) ] = [ q µ,β (1),, q µ,β (σ) ] Q µ,β [1, 1] Q µ,β [1, σ]... Q µ,β [σ, 1] Q µ,β [σ, σ] (S = {1,, σ}) Markov 2009 10 2 8 / 25

GA (q µ,β (x)) x S β µ GA µ, β Markov 2009 10 2 9 / 25

GA U := {x = (x 1,, x M ) S x 1 = = x M } U := {x = (x 1,, x M ) U f (x k ) = max f (i), k = 1,, M} i I Davis-Princepe, 1991 β > 0 Suzuki, 1998 lim q µ,β(x) > 0 = x U µ 0 lim lim q µ,β(x) > 0 = x U β µ 0 ( ) Markov 2009 10 2 10 / 25

Markov (Q α [x, y]) x,y S : α > 0 (q α (x)) x S : Q α q (x) := lim α q α (x), x S x S y S V (x y) := lim α 1 α log Q α[x, y] [0, ] S = {1,, σ} ( ) G(y): y S ( ) V (γ) := (x y) γ W (x) := V (x y), γ G(x) min V (γ) γ G(x) W min := min x S W (x) Markov 2009 10 2 11 / 25

Freidlin-Wentzell, 1984 Freidlin-Wentzell, 1984 Q α (x) := γ G(x) (u,z) γ 1 (Q α [x, y]) x,y S q α (x) = Q α [u, z] Q α (x) y S Q α(y), x S 2 lim α 1 α log q α(x) = W (x) W min x S q (x) > 0 = W (x) = W min Markov 2009 10 2 12 / 25

Cerf, 1998 Cert, 1998 S U α = α(µ, β) α µ 0, β S U L, M, f, µ, β W (x), x S\U > W (x), x U = S U Markov 2009 10 2 13 / 25

Albuquerque-Mazza, 2001 := max log f (i) log f (j) i,j I µ(β) = ϵ exp( λβ) 0 < ϵ < 1, λ > 0 f : I (0, ) 1 1 Albuquerque-Mazza, 2001 1 S U 2 λ > M = U S Markov 2009 10 2 14 / 25

:= max log f (i) log f (j) i,j I µ(β) = ϵ exp( λβ) 0 < ϵ < 1, λ > 0 f : I (0, ) 1 1 1 λ > M M 1 = U S λ > 2 M 2 GA Markov 2009 10 2 15 / 25

: 1 ( ) k {1,, L} 1 ( 1 M 0 ) 3 1 2 x y def C[x, y] > 0 Markov 2009 10 2 16 / 25

V (x y) x = (x 1,, x M ) S V (x) := M k=1 log f (x k) V (x y) = lim β 1 β log Q β[x, y] = min {λd(x, u) + V (y) min V (r)} u v,v y v r Markov 2009 10 2 17 / 25

V (x y) ( ) : M β [x, y] := µ(β) d(x,y) (1 µ(β)) LM d(x,y) > 0 g β (y k ) := f (y k ) β M k=1 f (x k) β C[x, y] > 0 S β [x, y] := { M k=1 g β(y k ), x y 0, x y Markov 2009 10 2 18 / 25

o(β) lim β β = 0 Q β [x, y] := V (x y) ( ) u,v S 1 β log Q β[x, y] := 1 β log{ M β [x, u]c[u, v]s β [v, y] u,v S = 1 β log u v,v y M β [x, u]c[u, v]s β [v, y]} exp{δ(u, v)β + o(β)} max δ(u, v) u v,v y = min {λd(x, u) + V (y) min V (r)} u v,v y v r Markov 2009 10 2 19 / 25

S U S S S + := S\S 2 1 x S + V (x y) = 0 y S 2 x S +, y S V (y x) > 0 = q (x) > 0 = x S S := U S + := S\U V (x y) = min {λd(x, u) + V (y) min V (r)} u v,v y v r 2 q (x) > 0 = x U Markov 2009 10 2 20 / 25

S U φ : S [0, ) def V (x y) [0, ) (x, y) S 2 V (x y) V (y x) = φ(y) φ(x) 1 φ : S (, ) x S q (x) = 0 = φ(x) > min y S φ(y) W V (x) = M log f (i), x = (i) U, i I S := U Markov 2009 10 2 21 / 25

S U ( ) V ((i) (j)) = f (i) > f (j) min {λd((i), u) + V (y) min V (r)} u v,v (j) v r 1 j j M 2 j M j M 3 j 1 f (i), f (j) M 1 j M min{λρ(i, j) + V ((j)) V ((i)), Mλρ(i, j), λ[ρ(i, j) + M 1]} V ((i) (j)) min{λρ(i, j) + V ((j)) V ((i)), Mλρ(i, j)} λ > M V ((i) (j)) = λρ(i, j) + V ((j)) V ((i)) M 1 Markov 2009 10 2 22 / 25

S U ( ) V ((i) (j)) V ((j) (i)) = M(log f (i) log f (j)) = V (j) V (i) f (i) f (j) V ((i) (j)) = λρ(i, j) f (i) > f (j),f (i) f (j) V ((i) (j)) V ((j) (i)) = V (j) V (i) ( ) Markov 2009 10 2 23 / 25

: M = 2 β f 1 1 i 1 i L i 1 i L M β i 1 i L i 1 i L C j 1 j L j 1 j L S β j 1 j L j 1 j L {i h, i h } = {j h, j h }, h = 1,, L Markov 2009 10 2 24 / 25

GA Markov 1 µ 0, β T 0 2 µ β 1 Albuquerque-Mazza, 2001 2 1 f : I (0, ) 1 1 2 Cerf, 1998 Markov 2009 10 2 25 / 25