Digital Signal Processing Reference
In-Depth Information
This property makes the first n terms of series in (2.79) equal to zero and this
reduces π n (z) to
n,m z −m−1 =
n,n+m z −n−m−1 .
π n (z) =
(2.82)
m=n
m=0
The expansion coe cients n,m from (2.82) can be computed recursively via
β n+1 n+1,m = n,m+1 −α n n,m −β n n−1,m
0,0 = 1
(2.83)
where the parameters{α n }and{β n }are the same Lanczos coupling constants
from (2.49). Employing (2.55) and (2.61), we can rewrite (2.81) as
n
q r,n−r r+m = 0
(0≤m < n)
(2.84)
r=0
or in the alternative matrix counterpart
0
1
0
1
0
1
0 1 2
n−1
q 0,n
q 1,n−1
q 2,n−2
.
q n−1,1
n
n+1
n+2
.
2n−1
@
A
@
A
@
A
1 2 3
n
n+1
. . . . . . .
n−1 n n+1 2n−2
2 3 4
=−
.
(2.85)
It is seen that the n×n matrix on the lhs of (2.85) represents the usual Hankel
matrix H n ( 0 )≡{ i+j }(0≤i≤n−1 , 0≤j≤n−1). Given the first 2n
moments{ r }, the system (2.85) of n linear inhomogeneous equations can
be solved by taking q n,n−r as the unknown. In particular, the solution of
the system (2.85) exists and it is unique for the nonzero value of the Hankel
determinant
det H n ( 0 ) = 0.
(2.86)
The relation (2.86) can be proven by supposing that, e.g., the opposite is valid,
det H n ( 0 ) = 0, and establishing the contradiction afterwards. The relation
det H n ( 0 ) = 0 means that there exists a linear dependence among the rows
of det H n ( 0 ).
Linear dependence signifies that there is a nonzero column
vector y ={y r
}(0≤r≤n−1) such that H n ( 0 )y = 0
0
@
1
A
0
@
1
A
0
@
1
A
0 1 2 n−1
1 2 3 n
2 3 4
y 0
y 1
y 2
.
y n−1
0
0
0
.
0
n+1
=
(2.87)
.
.
.
.
. . .
n−1 n n+1
2n−2
or alternatively
y T H n ( 0 )
y = 0
(2.88)
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