Approximation Of Functions of class by

Linear Operators

M. L. Mittal*, B. E. Rhoades** and Smita Sonker*

*Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, 247667 U.K. India

** Department of Mathematics, Indiana University, Bloomington, IN 47405-7106, USA

In Memory of Professor Brian Kuttner, 1908-1992

Abstract

Mittal and Rhoades (1999-2001), Mittal et al. (2005) Mittal, and Rhoades and Mishra (2006) have initiated the studies of error estimatesthrough trigonometric-Fourier approximation (tfa) for the situations in which the summability matrix T does not have monotone rows.In this paper, we continue the work in the direction. Here we extend two theorems of Leindler [L. Leindler, Trigonometric approximation in -norm,J. Math. Anal. Appl. 302 (2005) 129-136], where he has weakened the conditions on given by Chandra [P. Chandra, Trigonometric approximation of functions in -norm, J. Math. Anal. Appl. 275 (2002) 13-26], to more general classes of triangular matrix methods. Our Theorem also generalizes Theorem 4 partially of Mittal et al. [M.L. Mittal, et al., Using infinite matrices to approximate functions of class using trigonometric polynomials, J. Math. Anal. Appl. 326 (2007) 667-676] by dropping the monotonicity on the elements of matrix rows which in turn generalize the results of Quade [E. S. Quade, Trigonometric approximation in the mean, Duke Math. J. 3 (1937) 529-542].

Key words: Signals, Class, Trigonometric-Fourier approximation, -norm

  1. Introduction

Letdenote the nth term of the (C, 1) transform of the partial sums of the Fourier series of a - periodic function (signal) f. In 1937, Quade [15] has proved that if

forthen for either (i) and or (ii) and He also showed that, if then Chandra[2] has extended the work of Quade[15] and proved three theorems. In [2] among others the following theorems, where and denote the nth terms of the Nörlund and weighted mean transforms of the sequences of partial sums, respectively were proved.

Theorem A[2].Let and let be positive such that

. (1)

If either

(i) and (ii) is monotonic,

or

(i) and (ii) is non-decreasing. Then

(2)

Theorem B[2]. Letand letbe positive and non-decreasing with (1). Then

(3)

NOTE:

  1. Some of the estimates, as mentioned by Chandra [2, p.15] himself, are sharper than the results proved by Quade[15], Mohapatra and Russell[14], and by himself earlier [1] and also new[2, p.253], hence are interesting (in view of Leindler [4, p.130] also).

2. From the point of view of applications, the sharper estimates of infinite matrices, as Gil mentioned [3, p.176], are useful to get bounds for the lattice(occurs in solid state Physics) norms of matrix valued functions, and enable us to investigate perturbations of matrix valued functions and compare them. Few more applications are mentioned in section 2.

3. Here we shall use all the notations of Mittal et al.[11].

A positive sequence c is called almost monotone decreasing (increasing) if there exists a constant depending on the sequence c only, such that for all

Such sequences will be denoted by c and c respectively. A sequence which is either AMDS or AMIS is called almost monotone and will be denoted by c.

Leindler [4] extended Theorems A and B of Chandra [2] without monotonicity on. He proved:

Theorem C [4].Let and let be positive. If one of the conditions

(i) and

(ii) and (1) holds,

(iii) and

(iv) and (1) holds,

(v)

maintains, then (2) holds.

Theorem D [4]. Let If the positive satisfies (1) and the condition then (3) holds.

For a given signal let

denote the partial sum, a trigonometric polynomial of degree(or order) n, of the first terms of the Fourier series f.

Define

The Fourier series of signal f is said to be T –summable to s, if as

Throughout -a linear operator, will denote a lower triangular regular matrix with non-negative entrieswith row sums 1. Such a matrix T is said to have monotone rows if, for each n, is either non-increasing or non-decreasing in k,

The integral modulus of continuity of f is defined by

If, for,

then The -norm of f is defined by

We write

, ,

where, the Dirichlet Kernel of degree n.

[x]- the greatest integer contained in x,

Here, a signal (function) f is approximated by trigonometric polynomials of order (or degree) n and the degree of approximation is given by

in terms of n. This method of approximation is called trigonometric Fourier Approximation.

Recently Mittal et al. [11] have generalized two theorems A and B of Chandra ([2, Theorem 1 and a part of Theorem 2]) to more general classes of triangular matrix methods. They prove:

Theorem E [11]. Letand let T have monotone rows and satisfy

(4)

(i) If and T also satisfies

(5)

where , then

(6)

(ii) If then (6) is satisfied.

(iii) If and T also satisfies

(7)

then (6) is satisfied.

2. Mittal, Rhoades ([5]-[8]), Mittal et al. [9] and Mittal, Rhoades, Mishra [10] have obtained many resultson tfa (these approximations have assumed important new dimensions due to their wide applications in signal analysis [12], in general and in digital signal processing [13] in particular, in view of the classical Shannon sampling theorem), using summability methods without monotone rows of the matrix T: a digital filter. In this paper, we extend two theorems C and D of Leindler [4, Theorems 1 and 2] to more general classes of triangular matrix methods. Our Theorem1 also generalize partially Theorem E of Mittal et al. [11], respectively by dropping monotonicity on the elements of matrix rows (that is weakening the conditions on the filter, we improve the quality of the filter). We prove:

Theorem 1.Let and let be an infinite regular triangular matrix.

(i) If in k and satisfies

(8)

where , then (6) is satisfied.

(ii) If and or (9)

(iii) If ,, or (10)

(iv) If,, (11)

and also , (12)

hold then (6) is satisfied.

We note that:

(i). In case of Nörlund or weighted-matrix, condition (8)[or(12)] reduces to (1)[11, p.674], while conditions (9), (10) and (11) reduce to conditions (iii), (iv) and (v) of theorem C respectively. Thus our Theorem1 generalizes theorem C.

(ii). Further, it is easy to examine that the conditions of Theorem 1 claim less than the requirements of Theorem E for. For example, the condition on the sum in (9) is always satisfied if the sequence is non-decreasing in k, then using (12), we get

If is non-increasing in k and (12) holds then

is also true.

3. Lemmas

In order to prove our Theorem 1, we require the following lemmas:

Lemma 1 [15]. If then

Lemma 2 [15]. Let, for and Then

Lemma 3 [11]. Let T have monotone rows and satisfy (8). Then, for

Note: Since every monotone sequence is also an almost monotone, the proof of Lemma 3 is valid for the almost monotone (i.e. AMDS or AMIS) sequences.

4. Proof of Theorem 1.

Cases I. If Dropping the second term as the proof runs similar to the case (I) of Theorem E[11]. Let be AMS in k. Thus, using Lemmas 2 and 3, we get

(13)

hence

Case III. If Using Lemma 2, we get

So, it remains to show that

(15)

We may write

and thus, as we have

By Abel’s transformation, we get

Thus by triangle inequality, we find

(16)

But by direct computations, we have

Therefore by Lemma 1, we get

(17)

We note that

Thus

(18)

As in case (II) of proof of Theorem E[11, p.672], we write

(19)

Next we claim that

(20)

holds,. We verify it by mathematical induction.

For then inequality (20) reduces to equality i.e.

holds. Now let us suppose that (20) holds for i.e.

(21)

and we will show that (20) is true for So, let k=m+1. Using (21), we get

Thus (20) holds for Consequently (20) holds

Using (10), (12), (19) and (20), we find

Combining (16), (17), (18) and (22) yields (15). Thus, from (15) and (14), we get

CASE II. If For this, we first prove that the condition

(23)

As in case (III), using (20) and taking r:=[n/2] throughout in this case, we have

Interchanging the order of summation and using (9), we get

Now

Using arguments as inand (9), we obtain

Again interchanging the order of summation and using (9), we have


From (25)-(28), we get (23). Thus (14), (17) and Lemma 2 again yield (6).

CASE V. If Using (13), conditions (11), (12), convention, Abel’s transformation and the result of Quade [15] cited in the introduction, we obtain

This completes the proof of case (V) and consequently the proof of Theorem 1 is complete.

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