Geography Reference
In-Depth Information
The su cient condition
( x,y )
2 L
∂x 2
2 L
∂x∂y
H 2 :=
> 0
2 L
∂y∂x
2 L
∂y 2
or
H 2 =2 1+ λ 0
> 0
(23.153)
01+ λ
leads to the 2
2 Hesse matrix of second derivatives with respect to ( x , y )atthepoint( x, y )
to be positive-definite. Indeed the diagonal form of H 2 allows positive eigenvalues for 1 + λ =
×
+ r 0 (X
y 0 ) 2 1 / 2 .
x 0 ) 2 +(Y
End of Example.
In summary, we can make the following
Corollary 23.6 (minimal distance mapping of a point close to the circle).
Let ( X,Y ) R
2 be a point close to the circle S
r 0 . The point ( x, y ) S
r 0 is at minimal Euclidean
distance X x 2
to ( X,Y ) R
2 if
( x, y ) ∈{ X x 2
2 , ( x, y ) S
1
r 0
=min | ( X,Y ) R
(23.154)
and
r 0 ( X
x 0 )
(X
x = x 0 +
(23.155)
x 0 ) 2 +(Y
y 0 ) 2
r 0 ( Y − y 0 )
y = y 0 +
(X
(23.156)
x 0 ) 2 +(Y
y 0 ) 2
solves the optimization problem.
End of Corollary.
Example 23.4 (minimal distance mapping of a point close to the straight line L
1 , κ 0 =0 0 =0).
According to Fig. 23.36 we minimize the Euclidean distance d ( x,X )= X x of a given
point X ∈ R
2 and an unknown point x L
1 which is an element of the straight line
1 := x R
|y− y 0 =tan α 0 ( x − x 0 )
2
L
passing the point ( x 0 ,y 0 ) with α 0 as its orientation. Indeed by means of the Lagrange multiplier
λ the constrained optimal location of x
( x , y ) is generated by
2 +2 λ ( y
L ( x, y, λ ):=
X
x
ax
b )=min
x,y,λ
(23.157)
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