2.1. The Interpolation Polynomials: Expressions
The aim of the present subsection is to study a problem of interpolation on the unit circle, which can be considered an intermediate case between Lagrange and Hermite interpolation problems, the one appearing if we fix the Lagrange values on all the nodal points and we fix the values for the derivatives only on half of the nodes. As usual, when we interpolate on the unit circle , we work in the space of Laurent polynomials because of the density of in the space of continuous functions on . Due to the characteristics of the problem, we consider nodal systems with nodes that we denote by where for and for If we consider two sequences and , we pose the following problem:
Compute the Laurent polynomial
working in the subspace
with
p and
q non-negative integers such that
, and satisfying the interpolation conditions
For simplicity, we eliminate the second subindex in the notation of the nodal points as well as in the interpolation conditions. Thus, we write
, and
instead.
To solve this problem, we decompose it into two separate problems for which we introduce the following notation: We denote by
the Hermite–Fejér-type interpolation polynomial (Hermite–Fejér interpolation polynomial in the sequel) in the Laurent space
, satisfying the conditions
and we denote by
the polynomial in the Laurent space
, satisfying the conditions
It is clear that
If
F is a function defined on
and we take
for
, we denote by
the Hermite–Fejér interpolation polynomial related to
F and satisfying (
1). If
F is a regular function on an open set containing
and we take
, we denote the Laurent polynomial satisfying (
2) by
Thus,
When
for
and the values
for
are arbitrary, if we denote this vector of values by
, we write
Our first aim is to obtain the expressions of these interpolation polynomials when we use nodal systems more general than the equally spaced ones. Indeed, the case in which the nodal points are equally spaced was studied in [
15]. The novelty of the present paper is that the considered ones are not related to para-orthogonal polynomials on the unit circle, being only characterized by satisfying some suitable separation properties.
Throughout the paper, we denote the nodal polynomials by
and we use the factorization
with
and
Now, by taking into account the expressions given in [
15], we can state the following result:
Proposition 1. - (i)
The Hermite–Fejér interpolation polynomial satisfying (1) has the expressionwhereand - (ii)
The interpolation polynomial satisfying (2) has the expressionwhere
Proof. From [
15], we obtain expressions (
3) and (
4) with
,
and
, being
and
By doing some computations for the first term, we obtain
Proceeding in the same way for the rest, we obtain
and
Hence, we obtain the expressions for
, and
. □
The barycentric expressions of these interpolation polynomials are given below. They are very convenient for practical or numerical purposes (see [
18]).
Corollary 1. (i) The Hermite–Fejér interpolation polynomial satisfying (1) has the barycentric expression (ii) The interpolation polynomial satisfying (2) has the barycentric expression Proof. (i) It is obtained in the usual way, that is, by simplifying the common factors after dividing the expression of , given in Proposition 1, by the interpolation polynomial , which corresponds to constant function 1.
(ii) Proceeding in the same manner with leads to it. □
Remark 1. Since it is usual to choose the subspaces of Laurent polynomials in a balanced way, we take and . Thus, for n being even, we take along with and for n being odd, we take together with Without loss of generality, in what follows, we consider and develop the case in which n is even and thus we work in the space .
2.2. Nodal Systems: Properties and Auxiliary Results
We consider nodal systems
fulfilling the following separation property: there exists
such that for
, the length of the shortest arc between two consecutive nodes
and
, that we denote by
satisfies
where
. We assume that the nodes are numbered in clockwise order. We use Landau’s notation for complex sequences, writing that
if
is bounded. Thus, we write
. We will use the same
to denote different sequences. Unless otherwise mentioned explicitly, the limits we obtain from (
7) will be uniform.
So as to study the convergence behavior of the interpolation polynomials, we present below, in several lemmas, some properties related to the nodal system. Most of these properties are based on the following well-known relation between arcs and strings linked to the convex nature of the arcsin function:
For
, it holds that
Lemma 1. Let with satisfying separation property (7). Then, - (i)
- (ii)
There exists a positive constant such that for n large enough, - (iii)
Let us assume that z is not a nodal point and and are the nodal points nearest to z. Then, there exist positive constants K and E such thatand
Proof. (i) and (ii) See Proposition 1 in [
11].
(iii) It suffices to apply separation property (
7) and the mean value theorem. Notice that the result is valid for every
z, which is not a nodal point. It suffices to renumber the nodes in such a way that
and
are the nodal points nearest to
z. □
As an immediate consequence of the preceding lemma, we obtain certain properties for the polynomials
and
. They are similar to the former ones. Since
and
,
and
Therefore, from Lemma 1, we obtain the following lemma:
Lemma 2. - (i)
- (ii)
There exists a positive constant such that for n large enough, - (iii)
If we assume that z is not a nodal point and and are the nodal points nearest to z, then there exists a positive constant K such that
Proof. (i) and (ii) are obtained from Lemma 1 by using separation properties (
9) and (
10).
(iii) By applying the mean value theorem and (i), we have
We obtain the second inequality proceeding in a similar manner. □
We finish this subsection with some properties, which play an important role in the study of the convergence of the interpolation polynomials.
Lemma 3. There exists a positive constant such that for every n and for every , it holds that
Proof. (i) By applying Lemma 1, we have
where
is the
-partial sum of the harmonic series
.
(ii) It can be obtained in the same way as (i). To simplify the notation, we consider
n as even. Indeed, if we do the same, applying Lemmas 1 and 2, we obtain
□
In what follows, we bound and by and we denote , where A, B, and are the constants appearing in Lemmas 1 and 2.
Remark 2. In [17], it was proved property (11) when considering as nodal polynomials the para-orthogonal polynomials related to measures in the Szegő class with the Szegő function having analytic extension outside the unit disk (see [1,19]). Here, we have proved it by using only the separation properties satisfied by the nodal points. It is clear that those para-orthogonal polynomials in [17] also hold separation property (7). 2.3. Convergence of Hermite–Fejér and Hermite Interpolation in the Case of Continuous Functions
Proposition 2. There exists a positive constant such that for every function F bounded on , it holds thatfor every . Proof. The result can be obtained in a more general situation, that is, with
p and
q such that
, with
. Thus, we begin the proof in this general situation. It is clear that
By applying the preceding lemmas to the first summation, it holds that
Proceeding in the same way for the second one, it holds that
For simplicity, now we take
and apply Lemma 3, obtaining
for some positive constant
. Hence, from (
12) and (
13), we obtain that there exists
L such that
□
In order to prove convergence of the Hermite–Fejér interpolation polynomials related to some continuous functions, first, we recall the following definition and we present an auxiliary result.
The modulus of continuity of a given function continuous in a subset A of is .
Lemma 4. Let F be a continuous function on with the modulus of continuity when . Then, for each natural number N, there exists a Laurent polynomial and there exists with such that
Proof. This result is a consequence of Jackson’s theorem and the proof can be seen in Lemma 2 of [
15]. □
Proposition 3. Let F be a continuous function on with the modulus of continuity when . Then, converges to F uniformly on .
Proof. Let
n be large enough and
. Then, it holds that
and
. By the preceding lemma, we know that there exists
such that
with
. Then,
If we now apply Proposition 2, it holds that
for some constant
. The last inequality follows from the fact that the sequence
is bounded.
On the other hand,
By applying (
4) and the generalization of Markov’s inequality (see [
20]),
and we have, for
,
and for some constant
and since
we obtain
for some positive constant
Therefore, it goes to zero. □
Next, we study the complete problem, that is, the Hermite interpolation problem with nonvanishing conditions for the derivatives. In [
17], under suitable conditions for the nodal systems, it was given a sufficient condition on the derivatives, which cannot be improved, in order to obtain convergence for continuous functions. Now, we prove that other similar conditions work.
Proposition 4. Let F be a continuous function on with the modulus of continuity when and let . Then,
- (i)
If for some q, , then converges to F uniformly on .
- (ii)
If then converges to F uniformly on .
Proof. (i) If we apply expression (
4), we obtain
Firstly, we assume that
. In this case, we take
such that
and apply Lemma 3. Then, we obtain
Secondly, we assume that
. If we apply Lemmas 1 and 2, we have
for some positive constant
.
Hence, if we take into account the expression and Proposition 3, then the result is proven.
(ii) Proceeding in a similar way, we obtain
and taking into consideration our hypothesis, the result is proven. □
2.4. Interpolation of Smooth Functions: Convergence of the Interpolation Polynomials
Proposition 5. If F is an analytic function in an open annulus containing , then uniformly converges to F on and the order of convergence is for some r such that
Proof. We assume that
with
for some positive constant
P and
. Thus,
F can be expressed as
, where
Since
,
In this way, we have to study both absolute differences, that is,
for
For simplicity, we develop the case
.
Note that which goes to zero uniformly on .
In order to obtain
first, we compute
On the one hand, by taking into account Proposition 2, we obtain
On the other hand, since
according to (
4), by applying (
8) and Lemmas 2 and 3, it follows that
Hence,
and therefore
for some positive constant
Q.
Taking into account that
and
then
for some positive constant
T and thus it goes to zero uniformly on
.
The corresponding result for the absolute difference can be obtained in a similar way. □
Proposition 6. If is a function defined on with for some positive constant and , then converges to uniformly on . Moreover, the order of convergence is .
Proof. As we proceed as in the previous proposition, we write
, where
, and
are those given in (
14). Since
Thus, we have to study the behavior of
for
to obtain the uniform convergence of
to
F.
Indeed, if
,
and, by applying the integral test, it holds that
By taking into account (
15), we have
By applying the integral test again, we obtain
Hence, goes to zero and the order of convergence is . The term can be studied in a similar manner and finally the result follows. □
Remark 3. In [15], when considering the roots of unimodular complex numbers as nodal systems, we obtained similar results to those given in Propositions 5 and 6 although the order of convergence given in [15] is better than those. 2.5. The Case of the Bounded Interval
In this subsection, we consider very general nodal systems in the interval .
Let
n be even and let
be a nodal system ordered as follows:
with
and
. We also assume that the nodal points satisfy the separation property
with
a being a positive constant such that
Now, our aim is to solve the following interpolation problem, intermediate between those of Lagrange and Hermite on the interval :
Given two sequences of real numbers
and
, find an algebraic polynomial
satisfying
When
for
, with
f being a function defined on
, and
being arbitrary, we denote the interpolation polynomial satisfying (
17) by
. When
for
and
for
,
f being a differentiable function on
, we denote the corresponding interpolation polynomial by
.
To obtain the expression of the polynomial
satisfying (
17), first, we study the corresponding problem on
obtained through the Szegő transformation. By this transformation between
and
, which is
our real nodal system becomes
, where
and
that is,
. According to what was said, we will denote the corresponding nodal polynomial by
. Furthermore, since for
,
that is,
, we have
Clearly,
satisfies relation (
7) with
,
, and
Thus, the transformed problem is that of finding a polynomial
in the space
such that
In Proposition 1, we have given the expressions to compute the polynomial
satisfying (
18). Indeed, by taking into account that the nodal points are conjugated, the expressions can be simplified and it is immediate seeing that
has real coefficients. Thus, if we define
for
and
, then
fulfills that
for
Since
and
,
and therefore
where the last equality comes from the fact that
.
Since
, taking into account that
and applying L’Hôpital’s rule, we obtain that
. Proceeding in a similar way, we also obtain that
.
Since we cannot assure that
and
are equal to
and
, respectively, we modify
by adding two auxiliary polynomials to adjust the values in 1 and
. Thus, to obtain the polynomial
satisfying (
17), we consider the polynomials
and
satisfying the conditions
and
that is,
Hence, we obtain that the polynomial
fulfilling (
17) has the expression
Our next step is to study some convergence problems by applying the results obtained in the previous subsections. Thus, we have to transform the expression of the polynomial given above, for which purpose we begin by transforming and here.
Indeed, if we take into account that for and , then for , and, in particular, for and , it holds that and , respectively.
Moreover, if , then for and if then for
To relate these expressions to the nodal polynomials, we recall that
which implies that
and
which implies that
Hence, we obtain
- (i)
- (ii)
- (iii)
- (iv)
- (v)
- (vi)
Proposition 7. Let f be a continuous function on with when and let be the interpolation polynomial satisfying (17) with If or for some q such that , then the sequence uniformly converges to f on Proof. By using the Szegő transformation, we define a function F on by means of for .
Let us write
and denote by
the interpolation polynomial satisfying the conditions
If we write
and we take into account expression (
19), we obtain
Hence,
We study the behaviour of the first two terms in the last expression by applying Proposition 4. To carry this out, we take into account that
and
. Hence, under our hypothesis, we have
and then
for every
and
n large enough.
To study the last two terms, we take into account the following facts:
- (i)
and for q such that .
- (ii)
By applying Lemmas 1 and 2, we obtain that the polynomials
and
given in (
20) and (
21) can be bounded for every
, as
Therefore, it is immediate that and go to zero when n goes to ∞.
Finally, we use the same arguments as those of Theorem 6 in [
14] in the following way: We know that for an
n large enough, there exists
such that
and there exists
satisfying
with
. Therefore,
. Notice that for an
n large enough,
.
On the one hand, by applying twice the mentioned Markov’s inequalities, we obtain
Hence,
On the other hand, applying Markov’s inequality again, we obtain
and therefore
from which we deduce
and the same inequality for
. □
2.6. Interpolation of Smooth Functions: Convergence
Now, our objective is to study the rate of convergence for the interpolation polynomials related to smooth functions in the sense given in [
21]. Thus, first, we assume that
f is a function defined on
that can be written as
, where
for some positive constant
C and a natural number
t. In the expression,
denotes the Chebyshev polynomial of the first kind of degree
l.
To obtain the interpolation polynomial
satisfying (
17) with the nodal system fulfilling (
16), we decompose
f as follows:
where
and
Since
, we only need to compute
for
to obtain
.
Lemma 5. There exist positive constants and such that for every natural number l, Proof. We define a function
F on
by
and we compute the interpolation polynomial
where
being
and
.
Thus, we obtain that and therefore
By applying (
19) and taking into account that
and
, we have
where
From Proposition 2, we know that . Furthermore, we are in conditions to apply Proposition 4 since and . Hence, .
Therefore,
Now, we take into account that
By applying the aforementioned Markov’s inequality twice, we obtain that
and therefore
An analogous expression can be deduced for
.
Hence,
from which the result follows. □
Proposition 8. Let f be a function defined on by with for some positive constant C and a real number t such that . Then, converges to f uniformly on and the order of convergence is .
Proof. By using the decomposition of f, given at the beginning of this subsection, we have
On the one hand, we have which goes to 0 uniformly when n tends to ∞.
On the other hand, by applying Lemma 5, we obtain
By using the fact that
again, we obtain
which converges to 0 when
n tends to
□
Finally, we treat the case of analytic functions.
Proposition 9. Let f be an analytic function on that can be written as , where for some constant and . Then, converges to f uniformly on and the order of convergence is .
Proof. We write
, with
and
having the expressions given at the beginning of this subsection. Since
we have
On the one hand,
On the other hand, by applying Lemma 5, we obtain
which goes to zero when
n tends to
∞. □
Remark 4. The last results are similar to those given in [14], where we use the Chebyshev–Lobatto points as a nodal system. In that particular situation, the order of convergence is faster than those obtained in the present propositions, Propositions 8 and 9. 2.7. Numerical Experiments
This subsection is devoted to presenting some graphs related to the application of the method with the nodal systems dealt with. Actually, we have been interested in these types of nodal systems for some years. Notice that the different theories of interpolation have been developed based, in many cases, upon the roots of orthogonal polynomials; but this is a quite theoretical situation outside the equispaced nodal systems on
(closely connected with the four Chebyshev families on the bounded interval). Indeed, the separation property stated in (
7) was obtained as a result of the study of the roots of para-orthogonal polynomials with respect to a measure that is an analytical modification of the Lebesgue measure on the unit circle. But we can obtain a lot of nodal systems with the same property using mechanical models.
So, all our examples are related to nodal systems on
satisfying the separation property because of different origins and particular functions, which are interpolated using barycentric expressions (
5) and (
6). We use distinct nodal systems presented in two different papers, where they were studied in detail. We also use the parameters considered there. Next, we list the nodal systems and the functions that will be employed.
Our first example uses a measuring instrument based on a Cardan device. The full description of the nodal system and the proof that the system satisfies, (
7), can be found in [
11]. We choose
as the test function.
Our second example uses a measuring device based on a countdown process. The full description of the nodal system and the proof that it satisfies, (
7), can be found in [
11]. As the test function, we take
.
The third example is based on the analysis of certain positions of a natural satellite orbiting its planet. A detail description of the nodal system and the proof that (
7) is satisfied can be found in [
11]. We choose
as the test function.
Finally, we present an example that uses a nodal system constituted by the roots of a para-orthogonal polynomial with respect to a Bernstein–Szegő measure. The full description of the nodal system and the proof that it satisfies, (
7), can be found in [
19]. We select a jump function as the function to be approximated through interpolation.
In order to obtain a simple graphical representation, we always use a real-valued function with . All the graphs depict and the real part of the interpolation polynomial, the only component which has interest as a consequence of this piece of work. Thus, when considering with , all the graphs represent . In this case, it is easy to prove that the original interpolation conditions lead to zeroth-order contact points where the derivatives are not prescribed and first-order contact points where the derivatives are prescribed. In some cases, we use the Hermite–Fejér polynomial . In a similar way, the original interpolation conditions originate zeroth-order contact points where the derivatives are not prescribed and zeroth-order contact points where null values for the derivatives are prescribed. At these last nodes, will necessarily have a horizontal tangent.
Example 1. Our first example presents, in a graphical way, the peculiarities of and . We use a nodal system with nodes and . The objective function is . In Figure 1 below, is depicted in black and in red. We added the interpolation points in blue; notice that the region contains only 12 nodes. The only change below is that we represent instead of . The more relevant facts are
- 1.
The set of contact points between the objetive function and is a mix of zeroth-order contact points (even nodes, numbering in increasing order for the arguments, that is, starting from ) and first-order contact points (odd nodes, numbering in the same way).
- 2.
In a similar way, the contact points between the function and the real part of the Hermite–Fejér interpolant, which is , are zero-order contact ones. But at the odd nodes, it has a horizontal tangent.
Example 2. Our second example is included to show the convergence of the Hermite–Fejér interpolant and the interpolant , taking derivatives, and allowing us to satisfy the hypothesis of Proposition 4. We employ a nodal system with nodes and . The objective function is , a quite variable function near and (). In Figure 2 below, the function with , which is close to , is depicted in black. Furthermore, is depicted in red. We added the interpolation points in blue. Below, we represent, in a greater interval, and the function for . Near and , we take null values for the derivatives and far from both points, we use the derivatives of the function, allowing the hypothesis of Proposition 4 to be satisfied. Example 3. This example is considered to represent the convergence of corresponding to an analytical function on an open annulus containing . We use a nodal system with nodes and . The objective function is . In Figure 3, at the top, the function with is depicted in black and is depicted in red. The relevant fact is that both functions are indistinguishable. In the middle, we represent the difference between both functions to observe the accuracy. Finally, at the bottom, is represented in black when this value is less than or equal to , and in red for or in other cases; this gives a clear idea of the order of the error. Example 4. Our last example is included to present and when is the interpolated function, in which case they are equal. We use a 2n-node system with .
Note that the function is discontinuous and we have not developed a theory for these types of functions. Observing Figure 4, the more relevant facts are - 1.
Far from , we can intuit convergence.
- 2.
Near , a phenomenon similar to a Gibbs phenomenon with a singular aspect appears.