Abstract
In paper [R S Pathak and Ashish Pathak, Asymptotic expansion of Wavelet Transform for small value a , The Wavelet Transforms, World scientific, 164–168, (2009).], we presented a simple methode for deriving asymptotic expansion of wavelet transform \((W_\psi f) (b,a) = \frac{ a^{\frac{1}{2}}}{2\pi } \int _{-\infty }^{\infty } e^{ibw} \hat{f}(w) \overline{\hat{\psi }(aw)} dw \) with \(b \in \mathbb {R}\) for small values of a by considering the asymptotic expansion of \(\overline{\hat{\psi }}(w)\) and \(\hat{f}(w)\) as \( w \rightarrow 0 \) and \( w \rightarrow \infty \) respectively. In present paper, we consider the asymptotic expansion of \(\psi (t)\) as \( t \rightarrow \infty \) and f(t) as \(t\rightarrow 0 \) and then find the asymptotic expansion for small value a. Some example are given as illustration.
Similar content being viewed by others
Avoid common mistakes on your manuscript.
Introduction
Using Mellin transform technique of Wong and asymptotic expansions of the Fourier transform of the function and the wavelet Pathak and Pathak [1,2,3] have obtained the asymptotic expansions of the continuous wavelet transform for large and small values of dilation and translation parameters.
Lopez and Pagol [4] have obtained the asymptotic expansions of Mellin convolutions by means of analytic continuation and oscillatory case. Recently Pathak et al. [5] derived asymptotic expansion of continuous wavelet transform of the large value of dilation parameter by exploiting “sum and subtract method ” due to Lopez [4]. In this paper using same technique, we derive the asymptotic expansion of wavelet transform for small dilation parameter
In “Preliminaries” section we give some definition and technical results which are useful the further section. In “Main Results” section we introduce the main result of the paper. In “Example” section we shall compute asymptotic expansion of Mexican Hat wavelet transform and Morlet wavelet transform as a special case for small a.
Preliminaries
The general wavelet transform of f with respect to the wavelet \(\psi \) is defined by
provided the integral exists [6].
Using Fourier transform it can also be expressed as
where,
For deriving the asymptotic expansion of wavelet transform, we requir that \( f \in \mathbb {K}\) and \( \psi \in \mathbb {H} \); where
Definition 1
We denote by \(\mathbb {K}\) the set of function \(\psi \in L^{1}_{Loc} (0,\infty )\) satisfyings :
(i) \(\hat{\psi } \in L^{1}_{Loc} (0,\infty )\).
(ii) \(\psi (t)\) has an asymptotic expansion of the form:
where, \(0<\alpha <1\).
(iii) As \( \psi (t)= 0(t^{\rho _{1}}) ; as \,\, t\rightarrow 0+\) and \( \overline{\hat{\psi }}(w) = O(w^{-\rho _{1} -1}) ; as\, \rho _{1} \in \,\mathbb {R} , w\rightarrow \infty + .\)
If \(\psi \in \mathbb {K}\). Then by using [7, theorem 14, 323], we have the asymptotic expansion of \(\bar{\hat{\psi }}(w)\) as
Case I If \(0<\alpha <1\), then
where,
Case II If \(\alpha = 1\), we have
where,
for \(j= 0,1,2,3,\ldots \) and \(d_{j+1}= \lim _{z\rightarrow 0}\bigg [ \psi _{j+1,\, j+1}(w) + \frac{(-1)^{j}}{j!}\, b_{j} \log (w)\bigg ]\)
Definition 2
We denote by \(\mathbb {H}\) the set of function \(f \in L^{1}_{Loc} (0,\infty ) \) satisfying:
(i) f(t) is n times continuously differential in \((0,\infty )\) and \(\hat{f} \in L^{1}_{Loc} (0,\infty )\).
(ii) f(t) has an asymptotic expansion of the form
(iii) Each of the integral
converges uniformly for all sufficiently large w.
(iv) As
and
If \(f \in \mathbb {H}\) . Then by using [7, theorem 1, 199],We have an asymptotic expansion of \(\hat{f}(w)\) at \( w\rightarrow \infty + \) is
where, \( a^{*}_{k} = a_{k}\, e^{\frac{i\pi k}{2}}\, \Gamma (k)\).
Main Results
The following two theorem give the asymptotic expansion of \((W_{\psi } f)(b,a)\) at \(a\rightarrow 0+\) are:
Theorem 1
Let \( \psi \in \mathbb {K} \) , \( f \in \mathbb {H} \) , \(b \in \mathbb {R}-{0} \) and \(0<\alpha < 1\).Then for any \(j,k\in \mathbb {N}\) such that
K(k) is the index k for which \((j-k)\le 1<j-(k-1)\) and J(j) is the index j for which \((j-1)-k<1\le (j-k)\). Let M[g; z] denote the Mellin transform of g.
If \(j-k=1\), for some pair (j, k), then in formula (5), the corresponding sum of the terms
must be replace by
and the remainder term \(R_{n,m}(a)\) as \( a \rightarrow 0+\) is given
Proof
Define \(\hat{f_o}(w) = \hat{f}(w)\) and \(\bar{\hat{\psi _o}}(w)+ \overline{{\hat{\psi }}}_{\alpha -1}(w)= \overline{{\hat{\psi }}}(w)\). For any k, there exists j such that for \(0<\alpha <1\), we have \((k-1)-j<(k-1)-(j+\alpha -1)<1< k-(j-1)< k-(j+\alpha -2)\) . For given (k, j), the following integral exists:
In the following algorithms, we increase (k, j) step by step from (0, 0) to (n, m):
(a) For \(0<\alpha <1\) and (k, j) satisfying
do the following if \( (k-j)<1\), then \( k-(j+\alpha -1)<1\), go to (b); if \( (k-j)>1\), then \(k-(j+\alpha -1)>1\), go to (c) ; if \((k-j) = 1\), then \(k-(j+\alpha -1)>1\), go to (d).
(b). In this step, we take \(\hat{f_{k}}(w) = a^{*}_{k} w^{-k} + \hat{f}_{k+1}(w)\) in (9) and (iii) of Lemma 3 of [4],then for \(0<\alpha <1\) , we have
where,
Similarly by replacing w by \(-w\) , we get
go to (a) with k replaced by \(k+1\).
(c) we take
Now using (10) in (9) and (iii) of Lemma 2 of [4], we get
where,
Similarly by replacing w by \(-w\) , we get
Go to (a) with j replaced by \(j+1\).
(d) In these step, we take
where, \(\bar{\hat{\psi ^{1}_{j}}}(aw)= b^{*}_{j} (aw)^{j+\alpha -1} + \bar{\hat{\psi }}^{1}_{j+1}(aw) \) and \( \bar{\hat{\psi ^{2}_{j}}}(aw) = d^{*}_{j} (aw)^{j} + \bar{\hat{\psi }}^{2}_{j+1}(aw) \) . By using (11) and \(\hat{f}_{k}(w)= a^{*}_{k} w^{-k} + \hat{f}_{k+1}(w)\) in (9) and recall proof (d) of theorem 2 of [4], we get
Using \(a^{-z}= 1-z\log (a) + O(z^{2})\) ; when \(z\rightarrow 0^{+}\) and
We get
Similarly by replacing w by \(-w\) , we get
Go to (a) with j replaced by \(j+1\) and k replaced by \(k+1\).The error bounds for the remaninder \( R_{mn}(a)\) can be easly proof with the help of theorem 3 [4]. Hence this algorithm generates the required results (5)–(8). \(\square \)
Theorem 2
Let \( \psi \in \mathbb {K} \) , \( f \in \mathbb {H} \) , \(b \in \mathbb {R}-{0} \) and \(\alpha = 1\).Then for any \(j,k\in \mathbb {N}\) such that \((k-1)-j<1<k-(j-1)\),
K(k) is the index k for which \((j-k)\le 1<j-(k-1)\) and J(j) is the index j for which \((j-1)-k<1\le (j-k)\). Let M[g; z] denote the Mellin transform of g. If \(j-k= 1\) for some pair (j, k), then corresponding sum of the terms
must be replace by
and the remainder term \(R_{n,m}(a)\) as \( a \rightarrow 0+\) is given
Proof
Define \(\hat{f_o}(w) = \hat{f}(w)\) and \(\bar{\hat{\psi _o}}(w) = \overline{{\hat{\psi }}}(w)\). For any k, there exists j such that for \(\alpha =1\), we have \((k-1)-j< 1 < k-(j-1)\). For given (k, j), the following integral exists:
In the following algorithms, we increase (k, j) step by step from (0, 0) to (n, m):
(a). For \(\alpha = 1\) and (k, j) satisfying
do the following if \( (k-j)<1 \), go to (b); if \( (k-j)>1\), go to (c); if \((k-j) = 1\), go to (d). (b). In this step, we take \(\hat{f_{k}}(w) = a^{*}_{k} w^{-k} + \hat{f}_{k+1}(w)\) in (16) and (iii) of Lemma 3 of [4], we have
Similarly by replacing w by \(-w\) , we get
go to (a) with k replaced by \(k+1\).
(c). Here, we take
Now using (17) in (16) and (iii) of Lemma 2 of [4], we get
Similarly by replacing w by \(-w\) , we get
Go to (a) with j replaced by \(j+1\).
(d) In these step we take first \( \hat{f}_{k}(w)\) = \(a^{*}_{k} w^{-k} + \hat{f}_{k+1}(w)\) ; as \(w \rightarrow \infty \) and
Using (18) in (16) and recall proof (d) of Theorem 2 of [4], we get
Define the function
Therefore,
On the one hand \(\bar{\hat{\psi }}_{j}(w) = (c^{*}_{j} \log (w) + \gamma ^{*}_{j}) w^{j} + O(w^{j+1})\); when \(w\rightarrow 0^{+}\) and on the other hand \(\hat{f}_{k+1}(w)= - a^{*}_{k} w^{-k} + O(w^{-k-1}) \); when \(w\rightarrow 0^{+}\). Proceeding similar way [4], we get
Therefore,
Using \(a^{-z}= 1-z\log (a) + O(z^{2})\) ; when \(z\rightarrow 0^{+}\) and
We find that the above expression can be rewritten as
Similarly by replacing w by \(-w\) ,we get
Go to (a) with j replaced by \(j+1\) and k replaced by \(k+1\).The error bounds for the remaninder \( R_{nm} \) can be easly proof with the help of theorem 3 [4]. Hence this algorithm generates the required results (12)–(15). \(\square \)
Example
Using the aforesaid technique, we find the asymptotic expansions of Mexican Hat wavelet and Morlet wavelet transform.
Asymptotic Expansion of Mexican Hat Wavelet Transform
We consider \({\psi }(t) = (1-t^2)\,e^{\frac{-t^2}{2}}\) to be a Mexican Hat wavelet. Since Fourier transform of Mexican Hat \(\hat{\psi }(\omega )\) = \(\sqrt{2\pi } \,\omega ^{2}\,e^{\frac{-\omega ^2}{2}}\) is locally integrable in \(( -\infty ,\infty )\) and has an asymptotic expansion of \(\overline{\hat{\psi }}(\omega )\) as \(\omega \rightarrow 0^{+}\) [6]
where,
Now, assume \( f \in \mathbb {H}\) . Then by Theorem 2, and by means of formula [8, (10, 30), pp. 318, 320], we get the asymptotic expansion of Mexican Hat wavelet transform at \(a\rightarrow {0^{+}}\) is
K(k) is the index k for which \((2r-3)-k\le 1\le (2r-3)-(k-1)\). R(r) is the index r for which \((2r-2)-k\le 1\le (2r-3)- k\). If \((2r-3)-k = 1\), for some pair \((2r-3, k)\), then corresponding sum of the terms
must be replace by
Asymptotic Expansion of Morlet Wavelet Transform
we consider \(\psi (t)= e^{iw_ot -\frac{t^{2}}{2}}\) to be a Morlet wavelet. Since,Fourier transform of Morlet wavelet \(\hat{\psi }(w)= \sqrt{2\pi } w^{2} e^{-w^{2}/2}\) is locally integrable in \((-\infty , \infty )\) and has an asymptotic expansion of \(\bar{\hat{\psi }}(w)\) as \(w\rightarrow {0^{+}}\) is
where,
Now, assume \( f \in \mathbb {H}\) . Then by Theorem 2, and by means of formula [8, (11, 31), pp. 318, 320], we get the asymptotic expansion of Morlet wavelet transform at \(a\rightarrow {0^{+}}\) is
K(k) is the index k for which \((2r-1)-k\le 1\le (2r-1)-(k-1)\). R(r) is the index r for which \((2r-2)-k\le 1\le (2r-1)- k\). If \((2r-1)-k = 1\), for some pair \((2r-1, k)\), then corresponding sum of the terms
must be replace by
Conclusion
This paper focuses on the asymptotic expansion of continuous wavelet transform for small dilation parameter. The main advantage of this expansion is that the error terms can be easily and precisely calculated and these results are used to approximate analytical solution of different types of linear , non-linear , singular differential and integral equations which are related to the different types of wavelet transform. Apart from this direction, future work may involve seeking to apply the homotopy perturbation method, the variation iteration method or we can formed the suitable algorithm for solving the linear, non-linear , singular differential and integral equations. Another direction which can be further explored is that how to adjust the dilation parameter to priorities of different type of differential and integral equations. It is thus worth studying the properties of asymptotic expansion of different types of wavelet transform.
References
Pathak, R.S., Pathak, A.: Asymptotic Expansion of Wavelet Transform for Small Value a. The Wavelet Transforms, pp. 164–168. World Scientific, Singapore (2009)
Pathak, R.S., Pathak, A.: Asymptotic Expansion of Wavelet Transform with Error Term. The Wavelet Transforms, pp. 154–164. World Scientific, Singapore (2009)
Pathak, R.S., Pathak, A.: Asymptotic expansions of the wavelet transform for large and small values of b. Int. J. Math. Math. Sci. (2009). https://doi.org/10.1155/2009/270492
López, J.L., Pagola, P.: Asymptotic expansions of Mellin convolution integrals: an oscillatory case. J. Comput. Appl. Math. 233, 1562–1569 (2010)
Pathak, A., Yadav, P., Dixit, M.M.: An asymptotic expansion of continuous wavelet transform for large dilation parameter. Bol. Soc. Paran. Mat. 36(3), 27–39 (2018)
Debnath, L.: Wavelet Transforms and their Applications. Birkhäuser, Basel (2002)
Wong, R.: Asymptotic Approximations of Integrals. Academic Press, New York (1989)
Erde’lyi, A., Magnus, W., Oberhettinger, F., Tricomi, F.G.: Tables of Integral Transforms, vol. 1. McGraw-Hill, New York (1954)
Acknowledgements
The authors are thankful to the referee for his thorough review and highly appreciate the comments and suggestions to various improvements in the original version of the manuscript. The work of first author was supported by U.G.C. start-up grant No. F. 30-12/2014(BSR).
Funding
The work of first author was supported by U.G.C. start-up grant No. F. 30-12/2014(BSR).
Author information
Authors and Affiliations
Contributions
All authors read and approved the final manuscript.
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Pathak, A., Yadav, P. Asymptotic Expansion of Wavelet Transform for Small Values of a: An Oscillatory Case. Int. J. Appl. Comput. Math 8, 5 (2022). https://doi.org/10.1007/s40819-021-01158-4
Accepted:
Published:
DOI: https://doi.org/10.1007/s40819-021-01158-4