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This paper extends the existing theory of perfect reconstruction two-channel filter banks from bipartite graphs to non-bipartite graphs. By generalizing the concept of downsampling/upsampling we establish the frame of two-channel filter…

Information Theory · Computer Science 2023-04-04 Junxia You , Lihua Yang

In this work we propose the construction of two-channel wavelet filterbanks for analyzing functions defined on the vertices of any arbitrary finite weighted undirected graph. These graph based functions are referred to as graph-signals as…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-10-28 Sunil K. Narang , Antonio Ortega

We propose two-channel critically-sampled filter banks for signals on undirected graphs that utilize spectral domain sampling. Unlike conventional approaches based on vertex domain sampling, our transforms have the following desirable…

Signal Processing · Electrical Eng. & Systems 2019-01-23 Akie Sakiyama , Kana Watanabe , Yuichi Tanaka , Antonio Ortega

We propose novel two-channel filter banks for signals on graphs. Our designs can be applied to arbitrary graphs, given a positive semi definite variation operator, while using arbitrary vertex partitions for downsampling. The proposed…

Signal Processing · Electrical Eng. & Systems 2023-04-26 Eduardo Pavez , Benjamin Girault , Antonio Ortega , Philip A. Chou

In the past decade, several multi-resolution representation theories for graph signals have been proposed. Bipartite filter-banks stand out as the most natural extension of time domain filter-banks, in part because perfect reconstruction,…

Signal Processing · Electrical Eng. & Systems 2020-10-27 Eduardo Pavez , Benjamin Girault , Antonio Ortega , Philip A. Chou

In our recent work, we proposed the design of perfect reconstruction orthogonal wavelet filterbanks, called graph- QMF, for arbitrary undirected weighted graphs. In that formulation we first designed "one-dimensional" two-channel…

Information Theory · Computer Science 2015-06-11 Sunil K. Narang , Antonio Ortega

This paper proposes a class of $M$-channel spectral graph filter banks with a symmetric structure, that is, the transform has sampling operations and spectral graph filters on both the analysis and synthesis sides. The filter banks achieve…

Signal Processing · Electrical Eng. & Systems 2019-05-01 Akie Sakiyama , Kana Watanabe , Yuichi Tanaka

We investigate a scalable $M$-channel critically sampled filter bank for graph signals, where each of the $M$ filters is supported on a different subband of the graph Laplacian spectrum. For analysis, the graph signal is filtered on each…

Information Theory · Computer Science 2019-01-31 Shuni Li , Yan Jin , David I Shuman

In this paper, we present a structure for two-channel spline graph filter bank with spectral sampling (SGFBSS) on arbitrary undirected graphs. Our proposed structure has many desirable properties; namely, perfect reconstruction, critical…

Signal Processing · Electrical Eng. & Systems 2021-04-07 Amir Miraki , Hamid Saeedi-Sourck , Nicola Marchetti , Arman Farhang

In this work, we propose a class of spline-like wavelet filterbanks for graph signals. These filterbanks possess the properties of critical sampling and perfect reconstruction. Besides, the analysis filters are localized in the graph domain…

Signal Processing · Electrical Eng. & Systems 2024-10-28 Junxia You , Lihua Yang

To address the limitations of conventional critically sampled graph filter banks in joint time-vertex signal processing, which require decomposing the joint graph into bipartite subgraphs and thus cannot fully exploit all temporal and…

General Mathematics · Mathematics 2026-03-17 Yu Zhang , Bing-Zhao Li

Spectral Graph Neural Networks (GNNs), also referred to as graph filters have gained increasing prevalence for heterophily graphs. Optimal graph filters rely on Laplacian eigendecomposition for Fourier transform. In an attempt to avert the…

Machine Learning · Computer Science 2024-03-06 Keke Huang , Pietro Liò

Spectral Graph Neural Networks (GNNs), alternatively known as graph filters, have gained increasing prevalence for heterophily graphs. Optimal graph filters rely on Laplacian eigendecomposition for Fourier transform. In an attempt to avert…

Machine Learning · Computer Science 2024-05-22 Keke Huang , Yu Guang Wang , Ming Li , and Pietro Liò

Data are represented as graphs in a wide range of applications, such as Computer Vision (e.g., images) and Graphics (e.g., 3D meshes), network analysis (e.g., social networks), and bio-informatics (e.g., molecules). In this context, our…

Machine Learning · Computer Science 2021-04-27 Giuseppe Patanè

We design a critically-sampled compact-support biorthogonal transform for graph signals, via graph filterbanks. Instead of partitioning the nodes in two sets so as to remove one every two nodes in the filterbank downsampling operations, the…

Information Theory · Computer Science 2016-06-29 Nicolas Tremblay , Pierre Borgnat

The purpose of this work is the design of FIR QMF (Quadrature Mirror Filters) filters of perfect reconstruction and odd number of coefficients (even order). By design, these filters will have linear phase and integer delay. These filter…

Signal Processing · Electrical Eng. & Systems 2022-10-28 Fernando Martin-Rodriguez , Fernando Isasi-de-Vicente , Monica Fernandez-Barciela

We study the feasibility of short finite impulse response (FIR) synthesis for perfect reconstruction (PR) in generic FIR filter banks. Among all PR synthesis banks, we focus on the one with the minimum filter length. For filter banks with…

Information Theory · Computer Science 2015-05-27 Behzad Sharif , Yoram Bresler

Perfect reconstruction filter banks can be used to generate a variety of wavelet bases. Using IIR linear phase filters one can obtain symmetry properties for the wavelet and scaling functions. In this paper we describe all possible IIR…

Numerical Analysis · Mathematics 2011-12-23 Lucas Monzon

Graphs are mathematical tools that can be used to represent complex real-world interconnected systems, such as financial markets and social networks. Hence, machine learning (ML) over graphs has attracted significant attention recently.…

Machine Learning · Computer Science 2023-10-24 O. Deniz Kose , Yanning Shen , Gonzalo Mateos

The theory of group lifting structures is applied to linear phase lifting factorizations for the two nontrivial classes of two-channel linear phase perfect reconstruction filter banks, the whole- and half-sample symmetric classes. Group…

Information Theory · Computer Science 2013-10-11 Christopher M. Brislawn
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