Graph neural networks (GNNs) are popular weapons for modeling relational data. Existing
GNNs are not specified for attribute-incomplete graphs, making missing attribute imputation …

In this article, we establish theory of Parseval framelets associated to generalized
multiresolution analysis (GMRA) in the setting of reducing subspace for the local field of …

A constructive algorithm based on the theory of spectral pairs for constructing nonuniform
wavelet basis in L 2 (ℝ) L^2(\mathbbR) was considered by Gabardo and Nashed (J Funct …

Nonuniform nonhomogeneous dual wavelet frames in Sobolev spaces in $$L^2({\mathbb {K}})$$
| Afrika Matematika Skip to main content SpringerLink Account Menu Find a journal Publish …

Explicit construction of tight nonuniform framelet packets on local fields Page 1 Operators and
Matrices Volume 15, Number 1 (2021), 131–149 doi:10.7153/oam-2021-15-10 EXPLICIT …

In real life applications not all signals are obtained by uniform shifts; so there is a natural
question regarding analysis and decompositions of these types of signals by a stable …

Time-frequency analysis of signals had its origin almost 60 years ago, there have been
major developments of the time-scale and time-frequency analysis approach in the last few …

In this paper, we introduce the notion of nonhomogeneous dual wavelet frames in Sobolev
spaces over local fields. We provide the complete characterization of nonhomogeneous …

Tight wavelet frames are different from the orthonormal wavelets because of redundancy. By
sacrificing orthonormality and allowing redundancy, the tight wavelet frames become much …

Wavelet frames are different from the orthonormal wavelets because of redundancy. By
sacrificing orthonormality and allowing redundancy, wavelet frames become much easier to …