Physics Letters B 783 (2018) 421–427
Contents lists available at ScienceDirect
Physics Letters B
www.elsevier.com/locate/physletb
Enhanced symmetry of the p-adic wavelets
Parikshit Dutta
a,∗
, Debashis Ghoshal
b
, Arindam Lala
b,c
a
Asutosh College, 92 Shyama Prasad Mukherjee Road, Kolkata 700026, India
b
School of Physical Sciences, Jawaharlal Nehru University, New Delhi 110067, India
c
Instituto de Física, Pontificia Universidad Católica de Valparaíso, Casilla 4059, Valparaiso, Chile
a r t i c l e i n f o a b s t r a c t
Article history:
Received
26 June 2018
Accepted
5 July 2018
Available
online 10 July 2018
Editor:
N. Lambert
Wavelet analysis has been extended to the p-adic line Q
p
. The p-adic wavelets are complex valued
functions with compact support. As in the case of real wavelets, the construction of the basis functions is
recursive, employing scaling and translation. Consequently, wavelets form a representation of the affine
group generated by scaling and translation. In addition, p-adic wavelets are eigenfunctions of a pseudo-
differential
operator, as a result of which they turn out to have a larger symmetry group. The enhanced
symmetry of the p-adic wavelets is demonstrated.
© 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license
(http://creativecommons.org/licenses/by/4.0/). Funded by SCOAP
3
.
1. Introduction
Wavelet analysis may be considered as one of the cornerstones
of modern day multi-resolution analysis for linear and non-linear
processes. It is a useful method in the digital signal processing and
pattern recognition. However, wavelet analysis also finds applica-
tions
in pure mathematics [1], statistical data analysis [2], quantum
field theory [3], nonlinear dynamics [4], to name a few. It is ex-
tremely
useful in cases where traditional Fourier analysis is not
very efficient. This is because wavelets are localised in both time
and frequency, a property that resembles real life signals. In this
approach, functions are expanded in terms of a set of basis func-
tions
known as wavelet functions, which are compactly supported
in frequency and time domain. This allows for local processing of
functions independently at different scales.
The
mathematical description of wavelet theory begins with the
representation of a square integrable function in terms of a com-
plete
set of orthonormal basis (although in practical applications,
it is often more efficient to use a nonorthogonal set of functions).
The first basis of this type was introduced by Haar [5]for L
2
(
R
)
long before the notion of wavelet transform was developed. The
Haar wavelets, as they are called now, consist of dyadic translation
and dilatation of a basic compactly supported piecewise constant
function, known as the (Haar) mother wavelet function. Morlet and
Grossmass’s pioneering work on wavelet analysis [6]was based on
seismic wave data analysed by Morlet and collaborators and used
*
Corresponding author.
E-mail
addresses: parikshitdutta@yahoo.co.in (P. Dutta), dghoshal@mail.jnu.ac.in
(D. Ghoshal),
arindam.physics1@gmail.com (A. Lala).
smooth basis functions with compact support. Later work by Mal-
lat,
Meyer, Daubechies [7–10] and others developed the modern
theory of wavelet transform (see [11]for a brief historical review).
The
basis functions in wavelet analysis are constructed by ap-
plication
of scaling and translation on a mother wavelet, as a result
of which all the basis functions have the same shape. Let
M
(x) be
the mother wavelet. Then the scaled and translated functions are
a,b
(x) =
1
√
a
M
x −b
a
,
a ∈ R
+
and b ∈ R (1)
The functions
a,b
(x) may be thought to have resulted from
M
(x)
due to the action of the elements g(a, b), which satisfy
g(a
1
, b
1
) g(a
2
, b
2
) = g(a
1
a
2
, b
1
+a
1
b
2
) (2)
and thus form the affine group ‘ax +b’, a semi-direct product of the
group of scaling and translation. In this notation
M
(x) =
1,0
(x),
which for the Haar wavelet is
Haar
M
(x) =
⎧
⎪
⎨
⎪
⎩
+
1for0≤ x <
1
2
−1for
1
2
≤ x < 1
0otherwise
(3)
An orthonormal basis may be obtained by restricting the scaling
parameter a to, say, the dyadic numbers 2
n
(n ∈ Z), and the trans-
lation
parameter b ∈ Z. These are the original Haar wavelets. One
may also get an orthonormal set of basis wavelets in the interval
[
0
, 1
]
by restricting n to negative integers and translations appro-
priately.
The bases have the structure of a binary rooted tree with
the mother wavelet
1,0
at the base. In the first generation, we
https://doi.org/10.1016/j.physletb.2018.07.007
0370-2693/
© 2018 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Funded by
SCOAP
3
.