Vector-valued multiresolution analysis on local fields

Analysis ◽  
2014 ◽  
Vol 34 (4) ◽  
Author(s):  
Abdullah
Keyword(s):  
Multiresolution Analysis ◽  
Local Fields ◽  
Vector Valued

Vector-valued nonuniform multiresolution analysis on local fields

2015 ◽  
Vol 13 (04) ◽  
pp. 1550029 ◽  
Author(s):  
Firdous Ahmad Shah ◽  
M. Younus Bhat
Keyword(s):  
Multiresolution Analysis ◽  
Orthonormal Basis ◽  
Positive Characteristic ◽  
Local Fields ◽  
Sufficient Condition ◽  
Necessary And Sufficient Condition ◽  
Vilenkin Groups ◽  
Refinement Mask ◽  
Necessary And Sufficient ◽  
Vector Valued

A multiresolution analysis (MRA) on local fields of positive characteristic was defined by Shah and Abdullah for which the translation set is a discrete set which is not a group. In this paper, we continue the study based on this nonstandard setting and introduce vector-valued nonuniform multiresolution analysis (VNUMRA) where the associated subspace V0 of L2(K, ℂM) has an orthonormal basis of the form {Φ (x - λ)}λ∈Λ where Λ = {0, r/N} + 𝒵, N ≥ 1 is an integer and r is an odd integer such that r and N are relatively prime and 𝒵 = {u(n) : n ∈ ℕ0}. We establish a necessary and sufficient condition for the existence of associated wavelets and derive an algorithm for the construction of VNUMRA on local fields starting from a vector refinement mask G(ξ) with appropriate conditions. Further, these results also hold for Cantor and Vilenkin groups.

scholarly journals Vector valued nonuniform nonstationary wavelets and associated MRA on local fields

2021 ◽  
Vol 17 (2) ◽  
pp. 19-46
Author(s):  
O. Ahmad ◽  
A. H. Wani ◽  
N. A. Sheikh ◽  
M. Ahmad
Keyword(s):  
Multiresolution Analysis ◽  
Complete Characterization ◽  
Local Fields ◽  
Dimension Function ◽  
Vector Valued

Abstract In this paper we study nonstationary wavelets associated with vector valued nonuniform multiresolution analysis on local fields. By virtue of dimension function a complete characterization of vector valued nonuniform nonstationary wavelets is obtained.

Wavelet packets associated with linear canonical transform on spectrum

2021 ◽  
pp. 2150030
Author(s):  
M. Younus Bhat ◽  
Aamir H. Dar
Keyword(s):  
Fourier Transform ◽  
Multiresolution Analysis ◽  
Fourier Transforms ◽  
Fractional Fourier Transform ◽  
Integral Transforms ◽  
Wavelet Packets ◽  
Linear Canonical Transform ◽  
Fresnel Transform ◽  
The Fourier Transform ◽  
Vector Valued

The linear canonical transform (LCT) provides a unified treatment of the generalized Fourier transforms in the sense that it is an embodiment of several well-known integral transforms including the Fourier transform, fractional Fourier transform, Fresnel transform. Using this fascinating property of LCT, we, in this paper, constructed associated wavelet packets. First, we construct wavelet packets corresponding to nonuniform Multiresolution analysis (MRA) associated with LCT and then those corresponding to vector-valued nonuniform MRA associated with LCT. We investigate their various properties by means of LCT.

Study of High Dimensional Orthogonal Vector-Valued Wavelet with Scale 4

2013 ◽  
Vol 790 ◽  
pp. 665-668
Author(s):  
Wei Qing Yang
Keyword(s):  
Multiresolution Analysis ◽  
High Dimensional ◽  
Orthogonal Vector ◽  
Compactly Supported ◽  
Definition Of ◽  
Vector Valued

In this paper, we introduce the definition of vector-valued multiresolution analysis with scale 4 and orthogonal vector-valued wavelet with scale 4 is gived. The properties of compactly supported orthogonal vector-valued wavelets with scale 4 are proved.

A Feasible Algorithm for Designing Biorthogonal Binary Finitely Supported Multiwavelet Functions

2011 ◽  
Vol 225-226 ◽  
pp. 1092-1095
Author(s):  
Bao Min Yu
Keyword(s):  
Wavelet Analysis ◽  
Multiresolution Analysis ◽  
Natural Science ◽  
Matrix Theory ◽  
Scaling Functions ◽  
Science And Engineering ◽  
Engineering Computation ◽  
Feasible Algorithm ◽  
Definition Of ◽  
Vector Valued

Wavelet analysis has been a powerful tool for exploring and solving many complicated problems in natural science and engineering computation. In this paper, the notion of vector-valued multiresolution analysis is introduced and the definition of the biorthogonal vector-valued bivariate wavelet functions is given. The existence of biorthogonal vector-valued binary wavelet functions associated with a pair of biorthogonal vector-valued finitely supported binary scaling functions is investigated. An algorithm for constructing a class of biorthogonal vector-valued finitely supported binary wavelet functions is presented by virtue of multiresolution analysis and matrix theory.

The Information Optimal Algorithm Based on Poly-Scaled Wavelet Wraps and Wavelet Frames with Finite Support

2011 ◽  
Vol 204-210 ◽  
pp. 1759-1762
Author(s):  
Tong Qi Zhang
Keyword(s):  
Multiresolution Analysis ◽  
Operator Theory ◽  
Matrix Theory ◽  
Integral Transform ◽  
Optimal Algorithm ◽  
Higher Dimensions ◽  
Wavelet Frames ◽  
Finite Support ◽  
Multi Scale ◽  
Vector Valued

In this paper, we propose the notion of vector-valued multiresolution analysis and the vector-valued mutivariate wavelet wraps with multi-scale factor of spaceL2(Rn, Cv), which are ge- neralizations of multivariate wavelet wraps. An approach for designing a sort of biorthogonal vec- tor-valued wavelet wraps in higher dimensions is presented and their biorthogonality trait is charac- -terized by virtue of integral transform, matrix theory, and operator theory. Two biorthogonality formulas regarding these wavelet wraps are established.

scholarly journals ON THE CHARACTERIZATION OF SCALING FUNCTIONS ON NON-ARCHEMEDEAN FIELDS

2021 ◽  
Vol 7 (1) ◽  
pp. 3
Author(s):  
Ishtaq Ahmed ◽  
Owias Ahmad ◽  
Neyaz Ahmad Sheikh
Keyword(s):  
Multiresolution Analysis ◽  
Scaling Function ◽  
Real Life ◽  
Discrete Subgroup ◽  
Local Fields ◽  
Mathematical Tool ◽  
Spectral Pair ◽  
Spectral Pairs ◽  
The Given

In real life application all signals are not obtained from uniform shifts; so there is a natural question regarding analysis and decompositions of these types of signals by a stable mathematical tool.  This gap was filled by Gabardo and Nashed [11]   by establishing a constructive algorithm based on the theory of spectral pairs for constructing non-uniform wavelet basis in \(L^2(\mathbb R)\). In this setting, the associated translation set \(\Lambda =\left\{ 0,r/N\right\}+2\,\mathbb Z\) is no longer a discrete subgroup of \(\mathbb R\) but a spectrum associated with a certain one-dimensional spectral pair and the associated dilation is an even positive integer related to the given spectral pair. In this paper, we characterize the scaling function for non-uniform multiresolution analysis on local fields of positive characteristic (LFPC). Some properties of wavelet scaling function associated with non-uniform multiresolution analysis (NUMRA) on LFPC are also established.

scholarly journals A Short Note on Wavelet Frames Based on FMRA on Local Fields

2020 ◽  
Vol 2020 ◽  
pp. 1-5
Author(s):  
M. Younus Bhat
Keyword(s):  
Multiresolution Analysis ◽  
Positive Characteristic ◽  
Minimum Energy ◽  
Short Note ◽  
Explicit Construction ◽  
Local Fields ◽  
Wavelet Frame ◽  
Wavelet Frames ◽  
Frame Multiresolution Analysis ◽  
Field Of Positive Characteristic

The concept of frame multiresolution analysis (FMRA) on local fields of positive characteristic was given by Shah in his paper, Frame Multiresolution Analysis on Local Fields published by Journal of Operators. The author has studied the concept of minimum-energy wavelet frames on these prime characteristic fields. We continued the studies based on frame multiresolution analysis and minimum-energy wavelet frames on local fields of positive characteristic. In this paper, we introduce the notion of the construction of minimum-energy wavelet frames based on FMRA on local fields of positive characteristic. We provide a constructive algorithm for the existence of the minimum-energy wavelet frame on the local field of positive characteristic. An explicit construction of the frames and bases is given. In the end, we exhibit an example to illustrate our algorithm.

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