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  • 7/24/2019 Vector and Matrix Derivation

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    APPENDIX D

    VECTOR AND MATRIX

    D

    IFFERENTIAT

    I0

    N

    Definition D .l

    (Gradient) Let

    f

    x ) be a scalar finction

    of

    the elements of the vector

    z XI . .

    .

    X N ) ~ .

    hen, the gradient (v ec tor )

    off z)

    with respect

    to

    x is defined as

    The transpose of the gradient

    is

    the column vec tor

    DefinitionD.2

    (Hessian matrix) Let f x ) be a twice continuously diferentiable scalar

    function of the elements of the vector x XI X N ) ~ .hen, the Hessian matrix off x)

    65

    Parameter stimation

    f o r

    Scientists and ngineers

    by Adriaan van den

    Bos

    Copyright

    007

    John W iley Sons Inc.

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    66

    VECTOR ND M TRIX DIFFERENTI TION

    with respect to

    x

    is defined as

    Since, under the assumptions made, a x)/dx,dx,

    a

    x)/axqaxp,he Hessian

    matrix is symmetric.

    Dehition D3

    Jacobian ma trix) Let f

    x ) e

    a

    K

    x

    1 vectorfunction

    o

    he elements

    o

    he L x 1vector

    x.

    Then, the

    K

    x

    L

    Jacobian matrix

    of f x )

    with respect

    to

    x

    s

    defined as

    The transpose

    o

    the Jacobian matrix is

    Definition D.4 Let the elements

    of

    the M x

    N

    matrix

    A

    befunctions

    o

    the elements

    xqo

    a vector

    x.

    Then, the M x

    N

    matrix

    aA/dx,

    is defined as

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    67

    and the matrix of second-order derivatives as

    d2al l a2a lN

    ax,ax, ax,ax,

    ~

    Thus, the derivative of a matrix is the matrix

    of

    the derivatives.

    Theorem D.1 Product dzferentiation rule fo r matrices) Let A and B be an x M and

    an M x L matrix, respectively, and let C be the product matrix A

    B.

    Furthermore, suppose

    that the elements

    of A

    and B arefunctions

    of

    the elements

    xp f

    a vector

    x.

    Then,

    c

    ~

    bB

    B + A - - .

    ax, a x p ax,

    Proof By definition, the ( k ,C)-th elemen t

    of

    the matrix

    C

    is described by

    m=

    1

    Then, the product rule for differentiation yields

    and hence, by D.7),

    dC d A d B

    -B A -

    ax, ax, ax,

    D.10)

    D.11)

    D.12)

    This com pletes the proof.

    TheoremD 2 Let the

    N

    x N matrix A be nonsingular and let the elements of A befunctions

    of

    the elements

    xq

    f

    a

    vector

    x.

    Then, thefirs t-order and the second-order derivatives of

    the inverse A-' with respect to the elements of

    x

    are equal to, respectively,

    D.13)

    and

    2A-1 A- l (& A-1- d A 2 A

    I

    d A A - l f i ) A - l .

    D.14)

    ax,ax, ax ax ax axq ax ax

    Proof Differentiating AA-' I where I is the identity matrix of order N, yields

    where 0 is the N x N null matrix. Then,

    D.15)

    D.16)

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    68

    VECTOR ND M TRIX DIFFERENTI TION

    This

    expression shows that

    D.17)

    Applying Theorem

    D.

    to this expression yields

    Subsequently substituting the first order derivatives

    D.

    6 of A l in thisexpression shows

    that

    D.19)

    2A-1 A- l d A

    A - 1 - d A ___2 A a AA - l - ) 8 A A - l .

    ax,axg axp

    xg

    axpaxq

    axo axp

    This completes the proof.