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noncommutativity. Hence
[N (z) ’ C(z)]’1 ’ [W (z) ’ C(z)]’1
= [N (z) ’ C(z)]’1 (W (z) ’ N (z))[W (z) ’ C(z)]’1
= qC [pN qC ’ qN pC ]’1 (qN pW ’ pN qW )[qC pW ’ pC qW ]’1 qC
’1
™C ™
= z ’˜’m qC (z)q’1 pC qC (z):
Similarly, we ÿnd that
’1
™C ™
[E(z) ’ C(z)]’1 ’ [S(z) ’ C(z)]’1 = z ’˜’m qC (z)q’1 pC qC (z)
and hence (3.59) is established in its operator form. Complex multipliers are not used in it, and so
(3.59) holds as stated.

An important consequence of the compass identity is that, with z = 1, it becomes equivalent to the
vector epsilon algorithm for the construction of E(1) as we saw in the scalar case. If the elements
sj ∈ S have representation (3.14), there exists a scalar polynomial b(z) of degree k such that
f (z) = a(z)=b(z) ∈ Cd [[z]]: (3.60)
If the coe cients of b(z) are real, we can uniquely associate an operator f(z) with f (z) in (3.60),
and then the uniqueness theorem implies that
( j)
= f (1) (3.61)
2k

and we are apt to say that column 2k of the epsilon table is exact in this case. However, Example 3.2
indicates that the condition that b(z) must have real coe cients is not necessary. For greater gener-
ality in this respect, generalised inverse, vector-valued Padà approximants (GIPAs) were introduced
e
[n=2k]
(z) ∈ Cd [z] and a real scalar denominator
[22]. The existence of a vector numerator polynomial P
polynomial Q[n=2k] (z) having the following properties is normally established by (3.47) and (3.48):
deg{P [n=2k] (z)} = n; deg{Q[n=2k] (z)} = 2k;
(i) (3.62)

Q[n=2k] (z) is a factor of P [n=2k] (z):P [n=2k]— (z);
(ii) (3.63)

(iii) Q[n=2k] (0) = 1; (3.64)

f (z) ’ P [n=2k] (z)=Q[n=2k] (z) = O(z n+1 );
(iv) (3.65)
where the star in (3.63) denotes the functional complex-conjugate. These axioms su ce to prove
the following result.
72 P.R. Graves-Morris et al. / Journal of Computational and Applied Mathematics 122 (2000) 51“80


Theorem 3.10 (Uniqueness [24]). If the vector-valued Padà approximant
e
R[n=2k] (z) := P [n=2k] (z)=Q[n=2k] (z) (3.66)
of type [n=2k] for f (z) exists; then it is unique.

Proof. Suppose that
ˆ ˆ ˆ
R(z) = P(z)=Q(z); R(z) = P(z)= Q(z)
are two di erent vector-valued Padà approximants having the same speciÿcation as (3.62) “ (3.66).
e
ˆ
Let Qgcd (z) be the greatest common divisor of Q(z); Q(z) and deÿne reduced and coprime polyno-
mials by
ˆ ˆ
Qr (z) = Q(z)=Qgcd (z); Qr (z) = Q(z)=Qgcd (z):
From (3.63) and (3.65) we ÿnd that
ˆ—
ˆ
ˆ ˆ ˆ
z 2n+2 Qr (z)Qr (z) is a factor of [P(z)Qr (z) ’ P(z)Qr (z)] · [P — (z)Qr (z) ’ P (z)Qr (z)]: (3.67)
The left-hand expression of (3.67) is of degree 2n+4k ’2:deg{Qgcd (z)}+2. The right-hand expression
of (3.67) is of degree 2n + 4k ’ 2:deg{Qgcd (z)}. Therefore the right-hand expression of (3.67) is
identically zero.

ˆ [n=2m] (z) = b(z):b— (z) and P [n=2m] (z) = a(z)b— (z), the uniqueness theorem shows that the
ˆ
By taking Q
generalised inverse vector-valued Padà approximant constructed using the compass identity yields
e
f (z) = a(z)b— (z)=b(z)b— (z)
exactly. On putting z =1, it follows that the sequence S, such as the one given by (3.14), is summed
exactly by the vector epsilon algorithm in the column of index 2k. For normal cases, we have now
outlined the proof of a principal result [37,2].

Theorem 3.11 (McLeod™s theorem). Suppose that the vector sequence S satisÿes a nontrivial re-
cursion relation
k k
ÿi si+j = ÿi s ∞ ; j = 0; 1; 2; : : : (3.68)
i=0 i=0

with ÿi ∈ C. Then the vector epsilon algorithm leads to
( j)
= s∞ ; j = 0; 1; 2; : : : (3.69)
2k

provided that zero divisors are not encountered in the construction.

The previous theorem is a statement about exact results in the column of index 2k in the vector
epsilon table. This column corresponds to the row sequence of GIPAs of type [n=2k] for f (z),
evaluated at z = 1. If the given vector sequence S is nearly, but not exactly, generalized geometric,
we model this situation by supposing that its generating function f (z) is analytic in the closed unit
disk D, except for k poles in D := {z: |z| ¡ 1}. This hypothesis ensures that f (z) is analytic at
z = 1, and it is su ciently strong to guarantee convergence of the column of index 2k in the vector
P.R. Graves-Morris et al. / Journal of Computational and Applied Mathematics 122 (2000) 51“80 73


epsilon table. There are several convergence theorems of this type [28“30,39]. It is important to
note that any row convergence theorem for generalised inverse vector-valued Padà approximants has
e
immediate consequences as a convergence result for a column of the vector epsilon table.
A determinantal formula for Q[n=2k] (z) can be derived [24,25] by exploiting the factorisation prop-
erty (3.63). The formula is

0 M01 M02 ::: M0; 2k
M10 0 M12 ::: M1; 2k
. . . .
. . . .
Q[n=2k] (z) = ; (3.70)
. . . .
M2k’1; 0 M2k’1; 1 M2k’1; 2 ::: M2k’1; 2k
z 2k z 2k’1 z 2k’2 ::: 1

where the constant entries Mij are those in the ÿrst 2k rows of an anti-symmetric matrix M ∈ R(2k+1)—(2k+1)
deÿned by
±
 j’i’1

 H
c˜+i+n’2k+1 · cj’˜+n’2k for j ¿ i;



l=0
Mij =
 ’Mji for i ¡ j;





0 for i = j:
As a consequence of the compass identity (Theorem 3.9) and expansion (3.16), we see that entries
in the vector epsilon table are given by
( j)
= P [ j+2k=2k] (1)=Q[ j+2k=2k] (1); j; k¿0;
2k

From this result, it readily follows that each entry in the columns of even index in the vector epsilon
table is normally given succinctly by a ratio of determinants:
0 M01 ::: M0; 2k 0 M01 ::: M0; 2k
M10 0 ::: M1; 2k M10 0 ::: M1; 2k
. . . . . .
( j)
. . . . . .
= · :
. . . . . .
2k

M2k’1; 0 M2k’1; 1 ::: M2k’1; 2k M2k’1; 0 M2k’1; 1 ::: M2k’1; 2k
sj sj+1 ::: s2k+j 1 1 ::: 1

For computation, it is best to obtain numerical results from (3.4). The coe cients of Q[n=2k] (z) =
2k [n=2k] i
i=0 Qi z should be found by solving the homogeneous, anti-symmetric (and therefore consistent)
linear system equivalent to (3.70), namely

M q = 0;
[n=2k]
where qT = (Q2k’i ; i = 0; 1; : : : ; 2k).
74 P.R. Graves-Morris et al. / Journal of Computational and Applied Mathematics 122 (2000) 51“80


4. Vector-valued continued fractions and vector orthogonal polynomials
(0)
The elements 2k lying at the head of each column of even index in the vector epsilon table are
values of the convergents of a corresponding continued fraction. In Section 3, we noted that the
entries in the vector epsilon table are values of vector Padà approximants of
e
f (z) = c0 + c1 z + c2 z 2 + · · · (4.1)
as deÿned by (3.16). To obtain the continued fraction corresponding to (4.1), we use Viskova-
tov™s algorithm, which is an ingenious rule for e ciently performing successive reciprocation and
re-expansion of a series [2]. Because algebraic operations are required, we use the image of (4.1)
in A, which is
f(z) = c0 + c1 z + c2 z 2 + · · · (4.2)
with ci ∈ V. Using reciprocation and re-expansion, we ÿnd
C

J ’1
z J cJ z 1J ) zÿ1J ) z 2J ) zÿ2J )
( ( ( (
i
f(z) = ci z + ··· (4.3)
1’1’1’1’1’
i=0

with i( J ) ; ÿi( J ) ∈ A and provided all i( J ) = 0; ÿi( J ) = 0. By deÿnition, all the inverses implied in
(4.3) are to be taken as right-handed inverses. For example, the second convergent of (4.3) is
J ’1
(J)
’ zÿ1J ) ]’1 ]’1
(
ci z i + z J cJ [1 ’ z
[J + 1=1](z) = 1 [1
i=0

and the corresponding element of the vector epsilon table is
(J)
= [J + 1=1](1);
2

where the type refers to the allowed degrees of the numerator and denominator operator polynomials.
The next algorithm is used to construct the elements of (4.3).

Theorem 4.1 (The vector qd algorithm [40]). With the initialisation
ÿ0J ) = 0;
(
J = 1; 2; 3; : : : ; (4.4)
(J) ’1
= cJ cJ +1 ; J = 0; 1; 2; : : : ; (4.5)
1
(J) (J)
the remaining i ; ÿi can be constructed using
( J +1)
(J)
+ ÿmJ ) =
( ( J +1)
+ ÿm’1 ; (4.6)
m m

(J)
ÿmJ )
( ( J +1) ( J +1)
= ÿm (4.7)
m+1 m

for J = 0; 1; 2; : : : and m = 1; 2; 3; : : : :

Remark. The elements connected by these rules form lozenges in the ’ ÿ array, as in Fig. 8.
Rule (4.7) requires multiplications which are noncommutative except in the scalar case.
P.R. Graves-Morris et al. / Journal of Computational and Applied Mathematics 122 (2000) 51“80 75




Fig. 8.


Proof. First, the identity
C + z [1 + zÿD’1 ]’1 = C + z ’ z 2 ÿ[zÿ + D]’1 (4.8)
(J)
= ’ÿ1J ) ; ÿ = ’
( (J)
is applied to (4.3) with = cJ ; ÿ = ’ 1, then with 2, etc. We obtain
J
z J +1 cJ 1J )
(
z 2 ÿ1 J ) 2 J )
( (
i
f(z) = ci z + ··· : (4.9)
1 ’ z( 1J ) + ÿ1J ) ) ’ 1 ’ z( 2J ) + ÿ2J ) ) ’
( ( ( (
i=0
( J +1)
ÿ = ’ÿ1J +1) , then with
(
Secondly, let J ’ J + 1 in (4.3), and then apply (4.8) with =’ ;
1
= ’ 2J +1) ; ÿ = ’ÿ2J +1) , etc., to obtain
( (

J
z 2 1J +1) ÿ1J +1)

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