SlideShare una empresa de Scribd logo
1 de 71
Descargar para leer sin conexión
0   1
0              1

1.
     (n   M)
0                                    1

1.
     (n                 M)
2.
     (Fisher   g   α-        (α) )
0                                       1

1.
     (n                   M)
2.
     (Fisher    g α-            (α) )

3.             (M, g,   (α) )
0                                       1

1.
     (n                   M)
2.
     (Fisher    g α-            (α) )

3.             (M, g,   (α) )

4.
1 n             M   2

      p(x; ξ)
1 n                                     M           2

          p(x; ξ)

      M = p(x; ξ)|ξ = (ξ1 , · · · , ξn ) ∈ Ξ ⊂ Rn
                                         open

n
1 n                                               M           2

                      p(x; ξ)

                M = p(x; ξ)|ξ = (ξ1 , · · · , ξn ) ∈ Ξ ⊂ Rn
                                                   open

   n
(ξ1 , · · · , ξ n )                           M    n
1 n                                               M           2

                      p(x; ξ)

                M = p(x; ξ)|ξ = (ξ1 , · · · , ξn ) ∈ Ξ ⊂ Rn
                                                   open

   n
(ξ1 , · · · , ξ n )                           M    n
2   3
2   3
2.1 Fisher          4

M            gi j
2.1 Fisher                                   4

M                  gi j
                              ∂lξ ∂lξ
             gi j (ξ) :=Eξ
                              ∂ξi ∂ξ j


Eξ [ f ] := f (x)p(x; ξ)dx(        f     )
l(x; ξ) := log p(x; ξ)
2.1 Fisher                                               4

M                  gi j
                           ∂lξ ∂lξ
             gi j (ξ) :=Eξ
                           ∂ξi ∂ξ j
                           ∂l(x; ξ) ∂l(x; ξ)
                       =                     p(x; ξ)dx
                             ∂ξ i     ∂ξ j


Eξ [ f ] := f (x)p(x; ξ)dx(     f           )
l(x; ξ) := log p(x; ξ)
*1   5




*1   [3]
Fisher   6
Fisher                        6


              p(x; ξ)dx = 1

         ξi
7
(   )=0
       ∂
(   )= i   p(x; ξ)dx
      ∂ξ
7
(   )=0
       ∂
(   )= i       p(x; ξ)dx
      ∂ξ
            ∂
    =           p(x; ξ)dx
           ∂ξ i
7
(   )=0
       ∂
(   )= i       p(x; ξ)dx
      ∂ξ
            ∂
    =           p(x; ξ)dx
           ∂ξ i

           ∂l(x; ξ)
    =               p(x; ξ)dx
             ∂ξ  i
,                            8
    ∂l(x; ξ)
             p(x; ξ)dx = 0
      ∂ξ i
,                                 8
         ∂l(x; ξ)
                  p(x; ξ)dx = 0
           ∂ξ i



    ξj
9
(   )=0
        ∂      ∂l(x; ξ)
(   )=                  p(x; ξ)dx
       ∂ξ j      ∂ξi
           ∂ ∂l(x; ξ)
     =                   p(x; ξ) dx
          ∂ξ j    ∂ξ i

          ∂2 l(x; ξ)
     =                p(x; ξ)dx
           ∂ξ  j ∂ξ i

          ∂l(x; ξ) ∂l(x; ξ)
     +                       p(x; ξ)dx
            ∂ξi        ∂ξ j
10
∂l(x; ξ) ∂l(x; ξ)                 ∂2 l(x; ξ)
                  p(x; ξ)dx = −               p(x; ξ)dx
  ∂ξ i     ∂ξ j                    ∂ξ  j ∂ξ i
10
∂l(x; ξ) ∂l(x; ξ)                  ∂2 l(x; ξ)
                  p(x; ξ)dx = −                p(x; ξ)dx
  ∂ξ i     ∂ξ j                     ∂ξ  j ∂ξ i

 Fisher
                          ∂2 l(x; ξ)
            gi j (ξ) = −E                                  (1)
                           ∂ξ j ∂ξi
   (1)    Fisher
2.2 α-                                                        11

α∈R

   (α)          ∂2 l(x; ξ) 1 − α ∂l(x; ξ) ∂l(x; ξ) ∂l(x; ξ)
  Γi j,k   =E               +
                 ∂ξ  j ∂ξ i   2    ∂ξi      ∂ξ j     ∂ξk
2.2 α-                                                        11

α∈R

   (α)          ∂2 l(x; ξ) 1 − α ∂l(x; ξ) ∂l(x; ξ) ∂l(x; ξ)
  Γi j,k   =E               +
                 ∂ξ  j ∂ξ i   2    ∂ξi      ∂ξ j     ∂ξk
                        α-         (α)
                                     
                    
                              ∂    ∂ 
                                      
                   g
                    
                    
                    
                        (α)
                         ∂        , k  = Γ(α)
                                      
                                      
                                 j ∂ξ 
                        ∂ξi
                              ∂ξ           i j,k
2.3 α-                          12

1.       (torsion tensorT   )
2.3 α-                                                12

1.                  (torsion tensorT          )
2.    (−α)    (α)
                      (α)              (−α)
     (Xg(Y, Z) = g(   X Y, Z) + g(Y,   X Z)       )
2.3 α-                                                       12

1.                  (torsion tensorT               )
2.    (−α)    (α)
                      (α)               (−α)
     (Xg(Y, Z) = g(   X Y, Z) + g(Y,    X Z)            )
3. α = 0              α-       Fisher      g   Levi-Civita
2.4                                                        13


R : X(M) × X(M) × X(M)     (X, Y, Z) −→ R(X, Y)Z ∈ X(M)
         R(X, Y)Z :=   X   YZ   −   Y   XZ   −   [X,Y] Z

                                         (X, Y, Z           )

       (1,3)
14
    TpM     2                Πp                       {X, Y}


                            g(R(X, Y)Y, X)
          K(Π p ) :=
                     g(X, X) · g(Y, Y) − (g(X, Y))2
p
3   15
3.1                16

M:
g: M
  :g       M
               ∗

(M, g, )
3.2                                                         17

             p
                         n

                                                       
                        
                        
                        
                                  n                     
                                                        
                                                        
          p(x; θ) = exp C(x) +
                        
                        
                                       θ F s (x) − ϕ(θ)
                                         s              
                                                        
                                                        
                                  s=1

      C(x) ∈ F (X), F s (x)   0 ∈ F (X), ϕ(θ) ∈ F (Θ)


3.3
1.
2.                           18
3. Poisson
4. Gamma
5. Beta
6.
7.           etc.
                    Cauchy
19
3.4 Fisher              α-                                20
                                                     
                    
                    
                    
                                  n                   
                                                      
                                                      
      p(x; θ) = exp C(x) +
                    
                    
                                     θ F s (x) − ϕ(θ)
                                       s              
                                                      
                                                      
                                s=1



                            n
         l(x; θ) = C(x) +         θ s F s (x) − ϕ(θ)
                            s=1
θi , θ j                              21
               ∂i ∂ j l = −∂i ∂ j ϕ

Fisher     g
               gi j (θ) = ∂i ∂ j ϕ
θi , θ j                                   21
                    ∂i ∂ j l = −∂i ∂ j ϕ

Fisher          g
                    gi j (θ) = ∂i ∂ j ϕ


       Fisher
α-   22
α-                                                22
                                                 
                  
                  
                  
                            n                     
                                                  
                                                  
    p(x; θ) = exp C(x) +
                  
                  
                                 θ F s (x) − ϕ(θ)
                                   s              
                                                  
                                                  
                            s=1

x
α-                                                    22
                                                 
                  
                  
                  
                            n                     
                                                  
                                                  
    p(x; θ) = exp C(x) +
                  
                  
                                 θ F s (x) − ϕ(θ)
                                   s              
                                                  
                                                  
                            s=1

x
                                                  
      1               
                      
                      
                                     n             
                                                   
                                                   
1=                exp C(x) +
                      
                      
                                         θ F s (x) dx
                                           s       
                                                   
                                                   
   exp ϕ(θ)                         s=1
23
                                         
                 
                 
                 
                           n              
                                          
                                          
exp ϕ(θ) =   exp C(x) +
                 
                 
                                θ F s (x) dx
                                  s       
                                          
                                          
                           s=1
23
                                               
                       
                       
                       
                                 n              
                                                
                                                
     exp ϕ(θ) =    exp C(x) +
                       
                       
                                      θ F s (x) dx
                                        s       
                                                
                                                
                                 s=1

              θi            *2




*2
24
                  ∂ϕ
(   ) = exp ϕ(θ) · i (θ)
                  ∂θ
                                  
               
               
               
                        n          
                                   
                                   
(   )=         C(x) +
               
           exp           θ F s (x) Fi (x)e(ϕ(θ)−ϕ(θ)) dx
                           s       
                                   
                                  
                            s=1

          ϕ(θ)       C(x)+ n θ s F s (x)−ϕ(θ)
     =e          e         s=1                  Fi (x)dx

     = exp ϕ(θ) ·        p(x; θ)Fi (x)dx

     = exp ϕ(θ) · E [Fi ]
25
∂i ϕ = E [Fi ]   (   ∂i = ∂/∂θi )
25
     ∂i ϕ = E [Fi ]   (        ∂i = ∂/∂θi )



         exp ϕ · ∂i ϕ = exp ϕ · E [Fi ]

θj
26
(   ) = ∂ j (exp ϕ · ∂i ϕ)
     = ∂ j ∂i ϕ + ∂i ϕ · ∂ j ϕ
(   ) = ∂ j exp ϕ · E [Fi ]
     = (∂ j exp ϕ) · E [Fi ] + exp ϕ · (∂ j E [Fi ])
                                             A
A = ∂j      p(x; θ) · Fi dx
                                        27

  =      Fi ∂ j pdx

  =      Fi p · (F j − ∂ j ϕ)dx

  =      pFi F j dx −     Fi p∂ j ϕdx

  = E[Fi F j ] − ∂ j ϕE[Fi ]
28
= (∂ j exp ϕ) · E [Fi ] + exp ϕ · (E[Fi F j ] − ∂ j ϕE[Fi ])
= exp ϕ · E[Fi F j ]
28
= (∂ j exp ϕ) · E [Fi ] + exp ϕ · (E[Fi F j ] − ∂ j ϕE[Fi ])
= exp ϕ · E[Fi F j ]


             ∂i ∂ j ϕ + ∂i ϕ · ∂ j ϕ = E[Fi F j ]
28
  = (∂ j exp ϕ) · E [Fi ] + exp ϕ · (E[Fi F j ] − ∂ j ϕE[Fi ])
  = exp ϕ · E[Fi F j ]


                 ∂i ∂ j ϕ + ∂i ϕ · ∂ j ϕ = E[Fi F j ]



E[Fi F j Fk ] = ∂i ∂ j ∂k ϕ + ∂i ∂ j ϕ · ∂k ϕ
              + ∂ j ∂k ϕ · ∂i ϕ + ∂k ∂i ϕ · ∂ j ϕ + ∂i ϕ · ∂ j ϕ · ∂k ϕ
29
                        1−α
Γ(α)
 i j,k
         = E ∂i ∂ j l +     ∂i l · ∂ j l ∂k l
                         2
29
                        1−α
Γ(α)
 i j,k
         = E ∂i ∂ j l +     ∂i l · ∂ j l ∂k l
                         2


            1−α           1−α
 Γ(α)
  i j,k
          =     ∂i g jk =     ∂i ∂ j ∂k ϕ
             2             2
α-                                      30
     (α)       1−α
     ∂i j
         ∂   =     ∂ s gi j · g st ∂t
                2
4   31
4   31
4   31
4.1                                              32



                 1         (x − µ)2
      p(x; ξ) = √    exp −
                 2πσ         2σ2
                         (ξ = (µ, σ), µ ∈ R, σ ∈ R+ )
33
              x2 − 2µx + µ2      √
(   ) = exp −         2
                            − log 2πσ)
                   2σ
                 1      µ    µ2        √
     = exp −x 2
                     +x 2 −      + log( 2πσ)
                2σ 2   σ    2σ 2
33
              x2 − 2µx + µ2      √
(   ) = exp −         2
                            − log 2πσ)
                   2σ
                 1      µ    µ2        √
     = exp −x 2
                     +x 2 −      + log( 2πσ)
                2σ 2   σ    2σ 2

                                                 µ
    F1 (x) = −x2 ,F2 (x) = x,θ1 =    1
                                    2σ2
                                          θ2 =   σ2
33
               x2 − 2µx + µ2      √
(    ) = exp −         2
                             − log 2πσ)
                    2σ
                  1      µ    µ2        √
      = exp −x 2
                      +x 2 −      + log( 2πσ)
                 2σ 2   σ    2σ 2

                                                                 µ
     F1 (x) =   −x2 ,F   2 (x)   =   x ,θ 1   =    1
                                                  2σ2
                                                        θ2   =   σ2

            µ2        √       (θ2 )2 1    π
    ϕ(θ) =      + log( 2πσ) =       + log 1
           2σ 2                4θ 1  2    θ



      p(x; θ) = exp F1 (x)θ1 + F2 (x)θ2 − ϕ(θ)
θ ∈ Θ = θ = [θ1 , θ2 ]|θ1 ∈ R+ , θ2 ∈ R   34
4.2 Fisher          α-            35

Fisher
                   dµ2 + 2dσ2 3
             ds2 =           *
                       σ2




    *3
α-         ∂µ = ∂/∂µ, ∂σ = ∂/∂σ             36

           (α)       1−α
           ∂µ µ
               ∂   =     ∂σ
                      2σ
           (α)        (α)    1+α
           ∂µ σ
               ∂ =        ∂
                         =−
                      ∂σ µ
                                 ∂µ
                              σ
           (α)      1 + 2α
           ∂σ σ
               ∂ =−        ∂σ
                      σ
     α-
α-
                                1 − α2
          R(α) (∂µ , ∂σ )∂σ = −        ∂µ
                                  σ 2
37
                                     1 − α2 1
      g(R(α) (∂µ , ∂σ )∂σ , ∂µ ) = −        · 2
                                       σ2    σ
                                     1    2
g(X, X) · g(Y, Y) − (g(X, Y)) = 2 · 2 − 0
                                2
                                     σ σ
1−α2 2
     − σ4 σ4     = − c(α)                      38
                      2



     α-
           1−α2
          − 2                           *4




*4                               k

           R(X, Y)Z = k{g(Y, Z)X − g(X, Z)Y}
39

[1] Shun-Ichi Amari,Hiroshi Nagaoka Methods of
    Information Geometry Oxford University Press
[2]          ,
[3]
[4]          ,
40




Thank you very much
 for your attention!!

Más contenido relacionado

La actualidad más candente

Change of variables in double integrals
Change of variables in double integralsChange of variables in double integrals
Change of variables in double integralsTarun Gehlot
 
l1-Embeddings and Algorithmic Applications
l1-Embeddings and Algorithmic Applicationsl1-Embeddings and Algorithmic Applications
l1-Embeddings and Algorithmic ApplicationsGrigory Yaroslavtsev
 
Numerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis methodNumerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis methodAlexander Decker
 
[Vvedensky d.] group_theory,_problems_and_solution(book_fi.org)
[Vvedensky d.] group_theory,_problems_and_solution(book_fi.org)[Vvedensky d.] group_theory,_problems_and_solution(book_fi.org)
[Vvedensky d.] group_theory,_problems_and_solution(book_fi.org)Dabe Milli
 
Quantum modes - Ion Cotaescu
Quantum modes - Ion CotaescuQuantum modes - Ion Cotaescu
Quantum modes - Ion CotaescuSEENET-MTP
 
Solution of linear and nonlinear partial differential equations using mixture...
Solution of linear and nonlinear partial differential equations using mixture...Solution of linear and nonlinear partial differential equations using mixture...
Solution of linear and nonlinear partial differential equations using mixture...Alexander Decker
 
11.solution of linear and nonlinear partial differential equations using mixt...
11.solution of linear and nonlinear partial differential equations using mixt...11.solution of linear and nonlinear partial differential equations using mixt...
11.solution of linear and nonlinear partial differential equations using mixt...Alexander Decker
 
Reflect tsukuba524
Reflect tsukuba524Reflect tsukuba524
Reflect tsukuba524kazuhase2011
 
Research Inventy : International Journal of Engineering and Science
Research Inventy : International Journal of Engineering and ScienceResearch Inventy : International Journal of Engineering and Science
Research Inventy : International Journal of Engineering and Scienceinventy
 
Gaussseidelsor
GaussseidelsorGaussseidelsor
Gaussseidelsoruis
 
L. Jonke - A Twisted Look on Kappa-Minkowski: U(1) Gauge Theory
L. Jonke - A Twisted Look on Kappa-Minkowski: U(1) Gauge TheoryL. Jonke - A Twisted Look on Kappa-Minkowski: U(1) Gauge Theory
L. Jonke - A Twisted Look on Kappa-Minkowski: U(1) Gauge TheorySEENET-MTP
 
Intro probability 3
Intro probability 3Intro probability 3
Intro probability 3Phong Vo
 
The International Journal of Engineering and Science (The IJES)
The International Journal of Engineering and Science (The IJES)The International Journal of Engineering and Science (The IJES)
The International Journal of Engineering and Science (The IJES)theijes
 
Andreas Eberle
Andreas EberleAndreas Eberle
Andreas EberleBigMC
 

La actualidad más candente (19)

mathematics formulas
mathematics formulasmathematics formulas
mathematics formulas
 
Change of variables in double integrals
Change of variables in double integralsChange of variables in double integrals
Change of variables in double integrals
 
l1-Embeddings and Algorithmic Applications
l1-Embeddings and Algorithmic Applicationsl1-Embeddings and Algorithmic Applications
l1-Embeddings and Algorithmic Applications
 
Fdtd
FdtdFdtd
Fdtd
 
Numerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis methodNumerical solution of boundary value problems by piecewise analysis method
Numerical solution of boundary value problems by piecewise analysis method
 
[Vvedensky d.] group_theory,_problems_and_solution(book_fi.org)
[Vvedensky d.] group_theory,_problems_and_solution(book_fi.org)[Vvedensky d.] group_theory,_problems_and_solution(book_fi.org)
[Vvedensky d.] group_theory,_problems_and_solution(book_fi.org)
 
Chapter 3 (maths 3)
Chapter 3 (maths 3)Chapter 3 (maths 3)
Chapter 3 (maths 3)
 
Quantum modes - Ion Cotaescu
Quantum modes - Ion CotaescuQuantum modes - Ion Cotaescu
Quantum modes - Ion Cotaescu
 
Solution of linear and nonlinear partial differential equations using mixture...
Solution of linear and nonlinear partial differential equations using mixture...Solution of linear and nonlinear partial differential equations using mixture...
Solution of linear and nonlinear partial differential equations using mixture...
 
11.solution of linear and nonlinear partial differential equations using mixt...
11.solution of linear and nonlinear partial differential equations using mixt...11.solution of linear and nonlinear partial differential equations using mixt...
11.solution of linear and nonlinear partial differential equations using mixt...
 
Reflect tsukuba524
Reflect tsukuba524Reflect tsukuba524
Reflect tsukuba524
 
Research Inventy : International Journal of Engineering and Science
Research Inventy : International Journal of Engineering and ScienceResearch Inventy : International Journal of Engineering and Science
Research Inventy : International Journal of Engineering and Science
 
Gaussseidelsor
GaussseidelsorGaussseidelsor
Gaussseidelsor
 
Legendre Function
Legendre FunctionLegendre Function
Legendre Function
 
L. Jonke - A Twisted Look on Kappa-Minkowski: U(1) Gauge Theory
L. Jonke - A Twisted Look on Kappa-Minkowski: U(1) Gauge TheoryL. Jonke - A Twisted Look on Kappa-Minkowski: U(1) Gauge Theory
L. Jonke - A Twisted Look on Kappa-Minkowski: U(1) Gauge Theory
 
Intro probability 3
Intro probability 3Intro probability 3
Intro probability 3
 
The International Journal of Engineering and Science (The IJES)
The International Journal of Engineering and Science (The IJES)The International Journal of Engineering and Science (The IJES)
The International Journal of Engineering and Science (The IJES)
 
Andreas Eberle
Andreas EberleAndreas Eberle
Andreas Eberle
 
Week 11 - Trigonometry
Week 11 - TrigonometryWeek 11 - Trigonometry
Week 11 - Trigonometry
 

Similar a test

Jyokyo-kai-20120605
Jyokyo-kai-20120605Jyokyo-kai-20120605
Jyokyo-kai-20120605ketanaka
 
Dual Gravitons in AdS4/CFT3 and the Holographic Cotton Tensor
Dual Gravitons in AdS4/CFT3 and the Holographic Cotton TensorDual Gravitons in AdS4/CFT3 and the Holographic Cotton Tensor
Dual Gravitons in AdS4/CFT3 and the Holographic Cotton TensorSebastian De Haro
 
Formulario cuantica 2
Formulario cuantica 2Formulario cuantica 2
Formulario cuantica 2Abraham Prado
 
Additional notes EC220
Additional notes EC220Additional notes EC220
Additional notes EC220Guo Xu
 
Chapter 5(partial differentiation)
Chapter 5(partial differentiation)Chapter 5(partial differentiation)
Chapter 5(partial differentiation)Eko Wijayanto
 
Instantons and Chern-Simons Terms in AdS4/CFT3
Instantons and Chern-Simons Terms in AdS4/CFT3Instantons and Chern-Simons Terms in AdS4/CFT3
Instantons and Chern-Simons Terms in AdS4/CFT3Sebastian De Haro
 
Scattering theory analogues of several classical estimates in Fourier analysis
Scattering theory analogues of several classical estimates in Fourier analysisScattering theory analogues of several classical estimates in Fourier analysis
Scattering theory analogues of several classical estimates in Fourier analysisVjekoslavKovac1
 
Cosmin Crucean: Perturbative QED on de Sitter Universe.
Cosmin Crucean: Perturbative QED on de Sitter Universe.Cosmin Crucean: Perturbative QED on de Sitter Universe.
Cosmin Crucean: Perturbative QED on de Sitter Universe.SEENET-MTP
 
ฟังก์ชัน(function)
ฟังก์ชัน(function)ฟังก์ชัน(function)
ฟังก์ชัน(function)Yodhathai Reesrikom
 
Change of variables in double integrals
Change of variables in double integralsChange of variables in double integrals
Change of variables in double integralsTarun Gehlot
 
Peer instructions questions for basic quantum mechanics
Peer instructions questions for basic quantum mechanicsPeer instructions questions for basic quantum mechanics
Peer instructions questions for basic quantum mechanicsmolmodbasics
 
ฟังก์ชัน(function)
ฟังก์ชัน(function)ฟังก์ชัน(function)
ฟังก์ชัน(function)Yodhathai Reesrikom
 
tensor-decomposition
tensor-decompositiontensor-decomposition
tensor-decompositionKenta Oono
 
2 senarai rumus add maths k1 trial spm sbp 2010
2 senarai rumus add maths k1 trial spm sbp 20102 senarai rumus add maths k1 trial spm sbp 2010
2 senarai rumus add maths k1 trial spm sbp 2010zabidah awang
 
2 senarai rumus add maths k2 trial spm sbp 2010
2 senarai rumus add maths k2 trial spm sbp 20102 senarai rumus add maths k2 trial spm sbp 2010
2 senarai rumus add maths k2 trial spm sbp 2010zabidah awang
 

Similar a test (20)

Jyokyo-kai-20120605
Jyokyo-kai-20120605Jyokyo-kai-20120605
Jyokyo-kai-20120605
 
Holographic Cotton Tensor
Holographic Cotton TensorHolographic Cotton Tensor
Holographic Cotton Tensor
 
Dual Gravitons in AdS4/CFT3 and the Holographic Cotton Tensor
Dual Gravitons in AdS4/CFT3 and the Holographic Cotton TensorDual Gravitons in AdS4/CFT3 and the Holographic Cotton Tensor
Dual Gravitons in AdS4/CFT3 and the Holographic Cotton Tensor
 
Formulario cuantica 2
Formulario cuantica 2Formulario cuantica 2
Formulario cuantica 2
 
Additional notes EC220
Additional notes EC220Additional notes EC220
Additional notes EC220
 
Chapter 5(partial differentiation)
Chapter 5(partial differentiation)Chapter 5(partial differentiation)
Chapter 5(partial differentiation)
 
Instantons and Chern-Simons Terms in AdS4/CFT3
Instantons and Chern-Simons Terms in AdS4/CFT3Instantons and Chern-Simons Terms in AdS4/CFT3
Instantons and Chern-Simons Terms in AdS4/CFT3
 
Scattering theory analogues of several classical estimates in Fourier analysis
Scattering theory analogues of several classical estimates in Fourier analysisScattering theory analogues of several classical estimates in Fourier analysis
Scattering theory analogues of several classical estimates in Fourier analysis
 
Cosmin Crucean: Perturbative QED on de Sitter Universe.
Cosmin Crucean: Perturbative QED on de Sitter Universe.Cosmin Crucean: Perturbative QED on de Sitter Universe.
Cosmin Crucean: Perturbative QED on de Sitter Universe.
 
ฟังก์ชัน(function)
ฟังก์ชัน(function)ฟังก์ชัน(function)
ฟังก์ชัน(function)
 
Matrix calculus
Matrix calculusMatrix calculus
Matrix calculus
 
F.Komposisi
F.KomposisiF.Komposisi
F.Komposisi
 
Change of variables in double integrals
Change of variables in double integralsChange of variables in double integrals
Change of variables in double integrals
 
Peer instructions questions for basic quantum mechanics
Peer instructions questions for basic quantum mechanicsPeer instructions questions for basic quantum mechanics
Peer instructions questions for basic quantum mechanics
 
Funcion gamma
Funcion gammaFuncion gamma
Funcion gamma
 
Image denoising
Image denoisingImage denoising
Image denoising
 
ฟังก์ชัน(function)
ฟังก์ชัน(function)ฟังก์ชัน(function)
ฟังก์ชัน(function)
 
tensor-decomposition
tensor-decompositiontensor-decomposition
tensor-decomposition
 
2 senarai rumus add maths k1 trial spm sbp 2010
2 senarai rumus add maths k1 trial spm sbp 20102 senarai rumus add maths k1 trial spm sbp 2010
2 senarai rumus add maths k1 trial spm sbp 2010
 
2 senarai rumus add maths k2 trial spm sbp 2010
2 senarai rumus add maths k2 trial spm sbp 20102 senarai rumus add maths k2 trial spm sbp 2010
2 senarai rumus add maths k2 trial spm sbp 2010
 

Último

mini mental status format.docx
mini    mental       status     format.docxmini    mental       status     format.docx
mini mental status format.docxPoojaSen20
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdfSoniaTolstoy
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfsanyamsingh5019
 
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...anjaliyadav012327
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfchloefrazer622
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdfQucHHunhnh
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformChameera Dedduwage
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactdawncurless
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptxVS Mahajan Coaching Centre
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxiammrhaywood
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpinRaunakKeshri1
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsTechSoup
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactPECB
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingTechSoup
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdfQucHHunhnh
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 

Último (20)

mini mental status format.docx
mini    mental       status     format.docxmini    mental       status     format.docx
mini mental status format.docx
 
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdfBASLIQ CURRENT LOOKBOOK  LOOKBOOK(1) (1).pdf
BASLIQ CURRENT LOOKBOOK LOOKBOOK(1) (1).pdf
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdf
 
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
JAPAN: ORGANISATION OF PMDA, PHARMACEUTICAL LAWS & REGULATIONS, TYPES OF REGI...
 
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdf
 
1029-Danh muc Sach Giao Khoa khoi 6.pdf
1029-Danh muc Sach Giao Khoa khoi  6.pdf1029-Danh muc Sach Giao Khoa khoi  6.pdf
1029-Danh muc Sach Giao Khoa khoi 6.pdf
 
A Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy ReformA Critique of the Proposed National Education Policy Reform
A Critique of the Proposed National Education Policy Reform
 
Accessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impactAccessible design: Minimum effort, maximum impact
Accessible design: Minimum effort, maximum impact
 
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions  for the students and aspirants of Chemistry12th.pptxOrganic Name Reactions  for the students and aspirants of Chemistry12th.pptx
Organic Name Reactions for the students and aspirants of Chemistry12th.pptx
 
Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1Código Creativo y Arte de Software | Unidad 1
Código Creativo y Arte de Software | Unidad 1
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpin
 
Introduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The BasicsIntroduction to Nonprofit Accounting: The Basics
Introduction to Nonprofit Accounting: The Basics
 
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
Beyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global ImpactBeyond the EU: DORA and NIS 2 Directive's Global Impact
Beyond the EU: DORA and NIS 2 Directive's Global Impact
 
Advance Mobile Application Development class 07
Advance Mobile Application Development class 07Advance Mobile Application Development class 07
Advance Mobile Application Development class 07
 
Grant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy ConsultingGrant Readiness 101 TechSoup and Remy Consulting
Grant Readiness 101 TechSoup and Remy Consulting
 
1029 - Danh muc Sach Giao Khoa 10 . pdf
1029 -  Danh muc Sach Giao Khoa 10 . pdf1029 -  Danh muc Sach Giao Khoa 10 . pdf
1029 - Danh muc Sach Giao Khoa 10 . pdf
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 

test

  • 1.
  • 2. 0 1
  • 3. 0 1 1. (n M)
  • 4. 0 1 1. (n M) 2. (Fisher g α- (α) )
  • 5. 0 1 1. (n M) 2. (Fisher g α- (α) ) 3. (M, g, (α) )
  • 6. 0 1 1. (n M) 2. (Fisher g α- (α) ) 3. (M, g, (α) ) 4.
  • 7. 1 n M 2 p(x; ξ)
  • 8. 1 n M 2 p(x; ξ) M = p(x; ξ)|ξ = (ξ1 , · · · , ξn ) ∈ Ξ ⊂ Rn open n
  • 9. 1 n M 2 p(x; ξ) M = p(x; ξ)|ξ = (ξ1 , · · · , ξn ) ∈ Ξ ⊂ Rn open n (ξ1 , · · · , ξ n ) M n
  • 10. 1 n M 2 p(x; ξ) M = p(x; ξ)|ξ = (ξ1 , · · · , ξn ) ∈ Ξ ⊂ Rn open n (ξ1 , · · · , ξ n ) M n
  • 11. 2 3
  • 12. 2 3
  • 13. 2.1 Fisher 4 M gi j
  • 14. 2.1 Fisher 4 M gi j ∂lξ ∂lξ gi j (ξ) :=Eξ ∂ξi ∂ξ j Eξ [ f ] := f (x)p(x; ξ)dx( f ) l(x; ξ) := log p(x; ξ)
  • 15. 2.1 Fisher 4 M gi j ∂lξ ∂lξ gi j (ξ) :=Eξ ∂ξi ∂ξ j ∂l(x; ξ) ∂l(x; ξ) = p(x; ξ)dx ∂ξ i ∂ξ j Eξ [ f ] := f (x)p(x; ξ)dx( f ) l(x; ξ) := log p(x; ξ)
  • 16. *1 5 *1 [3]
  • 17. Fisher 6
  • 18. Fisher 6 p(x; ξ)dx = 1 ξi
  • 19. 7 ( )=0 ∂ ( )= i p(x; ξ)dx ∂ξ
  • 20. 7 ( )=0 ∂ ( )= i p(x; ξ)dx ∂ξ ∂ = p(x; ξ)dx ∂ξ i
  • 21. 7 ( )=0 ∂ ( )= i p(x; ξ)dx ∂ξ ∂ = p(x; ξ)dx ∂ξ i ∂l(x; ξ) = p(x; ξ)dx ∂ξ i
  • 22. , 8 ∂l(x; ξ) p(x; ξ)dx = 0 ∂ξ i
  • 23. , 8 ∂l(x; ξ) p(x; ξ)dx = 0 ∂ξ i ξj
  • 24. 9 ( )=0 ∂ ∂l(x; ξ) ( )= p(x; ξ)dx ∂ξ j ∂ξi ∂ ∂l(x; ξ) = p(x; ξ) dx ∂ξ j ∂ξ i ∂2 l(x; ξ) = p(x; ξ)dx ∂ξ j ∂ξ i ∂l(x; ξ) ∂l(x; ξ) + p(x; ξ)dx ∂ξi ∂ξ j
  • 25. 10 ∂l(x; ξ) ∂l(x; ξ) ∂2 l(x; ξ) p(x; ξ)dx = − p(x; ξ)dx ∂ξ i ∂ξ j ∂ξ j ∂ξ i
  • 26. 10 ∂l(x; ξ) ∂l(x; ξ) ∂2 l(x; ξ) p(x; ξ)dx = − p(x; ξ)dx ∂ξ i ∂ξ j ∂ξ j ∂ξ i Fisher ∂2 l(x; ξ) gi j (ξ) = −E (1) ∂ξ j ∂ξi (1) Fisher
  • 27. 2.2 α- 11 α∈R (α) ∂2 l(x; ξ) 1 − α ∂l(x; ξ) ∂l(x; ξ) ∂l(x; ξ) Γi j,k =E + ∂ξ j ∂ξ i 2 ∂ξi ∂ξ j ∂ξk
  • 28. 2.2 α- 11 α∈R (α) ∂2 l(x; ξ) 1 − α ∂l(x; ξ) ∂l(x; ξ) ∂l(x; ξ) Γi j,k =E + ∂ξ j ∂ξ i 2 ∂ξi ∂ξ j ∂ξk α- (α)     ∂ ∂   g    (α) ∂ , k  = Γ(α)   j ∂ξ  ∂ξi ∂ξ i j,k
  • 29. 2.3 α- 12 1. (torsion tensorT )
  • 30. 2.3 α- 12 1. (torsion tensorT ) 2. (−α) (α) (α) (−α) (Xg(Y, Z) = g( X Y, Z) + g(Y, X Z) )
  • 31. 2.3 α- 12 1. (torsion tensorT ) 2. (−α) (α) (α) (−α) (Xg(Y, Z) = g( X Y, Z) + g(Y, X Z) ) 3. α = 0 α- Fisher g Levi-Civita
  • 32. 2.4 13 R : X(M) × X(M) × X(M) (X, Y, Z) −→ R(X, Y)Z ∈ X(M) R(X, Y)Z := X YZ − Y XZ − [X,Y] Z (X, Y, Z ) (1,3)
  • 33. 14 TpM 2 Πp {X, Y} g(R(X, Y)Y, X) K(Π p ) := g(X, X) · g(Y, Y) − (g(X, Y))2 p
  • 34. 3 15
  • 35. 3.1 16 M: g: M :g M ∗ (M, g, )
  • 36. 3.2 17 p n      n    p(x; θ) = exp C(x) +    θ F s (x) − ϕ(θ) s    s=1 C(x) ∈ F (X), F s (x) 0 ∈ F (X), ϕ(θ) ∈ F (Θ) 3.3 1.
  • 37. 2. 18 3. Poisson 4. Gamma 5. Beta 6. 7. etc. Cauchy
  • 38. 19
  • 39. 3.4 Fisher α- 20      n    p(x; θ) = exp C(x) +    θ F s (x) − ϕ(θ) s    s=1 n l(x; θ) = C(x) + θ s F s (x) − ϕ(θ) s=1
  • 40. θi , θ j 21 ∂i ∂ j l = −∂i ∂ j ϕ Fisher g gi j (θ) = ∂i ∂ j ϕ
  • 41. θi , θ j 21 ∂i ∂ j l = −∂i ∂ j ϕ Fisher g gi j (θ) = ∂i ∂ j ϕ Fisher
  • 42. α- 22
  • 43. α- 22      n    p(x; θ) = exp C(x) +    θ F s (x) − ϕ(θ) s    s=1 x
  • 44. α- 22      n    p(x; θ) = exp C(x) +    θ F s (x) − ϕ(θ) s    s=1 x   1    n    1= exp C(x) +    θ F s (x) dx s    exp ϕ(θ) s=1
  • 45. 23      n    exp ϕ(θ) = exp C(x) +    θ F s (x) dx s    s=1
  • 46. 23      n    exp ϕ(θ) = exp C(x) +    θ F s (x) dx s    s=1 θi *2 *2
  • 47. 24 ∂ϕ ( ) = exp ϕ(θ) · i (θ) ∂θ      n    ( )= C(x) +  exp  θ F s (x) Fi (x)e(ϕ(θ)−ϕ(θ)) dx s     s=1 ϕ(θ) C(x)+ n θ s F s (x)−ϕ(θ) =e e s=1 Fi (x)dx = exp ϕ(θ) · p(x; θ)Fi (x)dx = exp ϕ(θ) · E [Fi ]
  • 48. 25 ∂i ϕ = E [Fi ] ( ∂i = ∂/∂θi )
  • 49. 25 ∂i ϕ = E [Fi ] ( ∂i = ∂/∂θi ) exp ϕ · ∂i ϕ = exp ϕ · E [Fi ] θj
  • 50. 26 ( ) = ∂ j (exp ϕ · ∂i ϕ) = ∂ j ∂i ϕ + ∂i ϕ · ∂ j ϕ ( ) = ∂ j exp ϕ · E [Fi ] = (∂ j exp ϕ) · E [Fi ] + exp ϕ · (∂ j E [Fi ]) A
  • 51. A = ∂j p(x; θ) · Fi dx 27 = Fi ∂ j pdx = Fi p · (F j − ∂ j ϕ)dx = pFi F j dx − Fi p∂ j ϕdx = E[Fi F j ] − ∂ j ϕE[Fi ]
  • 52. 28 = (∂ j exp ϕ) · E [Fi ] + exp ϕ · (E[Fi F j ] − ∂ j ϕE[Fi ]) = exp ϕ · E[Fi F j ]
  • 53. 28 = (∂ j exp ϕ) · E [Fi ] + exp ϕ · (E[Fi F j ] − ∂ j ϕE[Fi ]) = exp ϕ · E[Fi F j ] ∂i ∂ j ϕ + ∂i ϕ · ∂ j ϕ = E[Fi F j ]
  • 54. 28 = (∂ j exp ϕ) · E [Fi ] + exp ϕ · (E[Fi F j ] − ∂ j ϕE[Fi ]) = exp ϕ · E[Fi F j ] ∂i ∂ j ϕ + ∂i ϕ · ∂ j ϕ = E[Fi F j ] E[Fi F j Fk ] = ∂i ∂ j ∂k ϕ + ∂i ∂ j ϕ · ∂k ϕ + ∂ j ∂k ϕ · ∂i ϕ + ∂k ∂i ϕ · ∂ j ϕ + ∂i ϕ · ∂ j ϕ · ∂k ϕ
  • 55. 29 1−α Γ(α) i j,k = E ∂i ∂ j l + ∂i l · ∂ j l ∂k l 2
  • 56. 29 1−α Γ(α) i j,k = E ∂i ∂ j l + ∂i l · ∂ j l ∂k l 2 1−α 1−α Γ(α) i j,k = ∂i g jk = ∂i ∂ j ∂k ϕ 2 2
  • 57. α- 30 (α) 1−α ∂i j ∂ = ∂ s gi j · g st ∂t 2
  • 58. 4 31
  • 59. 4 31
  • 60. 4 31
  • 61. 4.1 32 1 (x − µ)2 p(x; ξ) = √ exp − 2πσ 2σ2 (ξ = (µ, σ), µ ∈ R, σ ∈ R+ )
  • 62. 33 x2 − 2µx + µ2 √ ( ) = exp − 2 − log 2πσ) 2σ 1 µ µ2 √ = exp −x 2 +x 2 − + log( 2πσ) 2σ 2 σ 2σ 2
  • 63. 33 x2 − 2µx + µ2 √ ( ) = exp − 2 − log 2πσ) 2σ 1 µ µ2 √ = exp −x 2 +x 2 − + log( 2πσ) 2σ 2 σ 2σ 2 µ F1 (x) = −x2 ,F2 (x) = x,θ1 = 1 2σ2 θ2 = σ2
  • 64. 33 x2 − 2µx + µ2 √ ( ) = exp − 2 − log 2πσ) 2σ 1 µ µ2 √ = exp −x 2 +x 2 − + log( 2πσ) 2σ 2 σ 2σ 2 µ F1 (x) = −x2 ,F 2 (x) = x ,θ 1 = 1 2σ2 θ2 = σ2 µ2 √ (θ2 )2 1 π ϕ(θ) = + log( 2πσ) = + log 1 2σ 2 4θ 1 2 θ p(x; θ) = exp F1 (x)θ1 + F2 (x)θ2 − ϕ(θ)
  • 65. θ ∈ Θ = θ = [θ1 , θ2 ]|θ1 ∈ R+ , θ2 ∈ R 34
  • 66. 4.2 Fisher α- 35 Fisher dµ2 + 2dσ2 3 ds2 = * σ2 *3
  • 67. α- ∂µ = ∂/∂µ, ∂σ = ∂/∂σ 36 (α) 1−α ∂µ µ ∂ = ∂σ 2σ (α) (α) 1+α ∂µ σ ∂ = ∂ =− ∂σ µ ∂µ σ (α) 1 + 2α ∂σ σ ∂ =− ∂σ σ α- α- 1 − α2 R(α) (∂µ , ∂σ )∂σ = − ∂µ σ 2
  • 68. 37 1 − α2 1 g(R(α) (∂µ , ∂σ )∂σ , ∂µ ) = − · 2 σ2 σ 1 2 g(X, X) · g(Y, Y) − (g(X, Y)) = 2 · 2 − 0 2 σ σ
  • 69. 1−α2 2 − σ4 σ4 = − c(α) 38 2 α- 1−α2 − 2 *4 *4 k R(X, Y)Z = k{g(Y, Z)X − g(X, Z)Y}
  • 70. 39 [1] Shun-Ichi Amari,Hiroshi Nagaoka Methods of Information Geometry Oxford University Press [2] , [3] [4] ,
  • 71. 40 Thank you very much for your attention!!