Graph QMF with flatness constraints

Author

Tay, David B. H. ; Lin, Zhiping

Author_Institution

Dept. of Electron. Eng., LaTrobe Univ., Bundoora, VIC, Australia

fYear

2015

fDate

24-27 May 2015

Firstpage

2600

Lastpage

2603

Abstract

Graph signal processing is an emerging area that has a wide variety of applications, e.g. energy networks, transportation networks and neuronal networks. Narang and Ortega (2012) proposed the critically sampled two-channel filter bank for signals on undirected graphs using spectral graph theory. The design of graph QMF (Quadrature-Mirror-Filters) by Narang and Ortega (2012) is based on the Chebyshev polynomial approximation of the ideal Meyer function. The reconstruction error using this method can be quite large especially for low degree filters and the high-pass filters suffer from DC leakage. A simple method that is analytically based is presented here for the design of the graph QMF without DC leakage and with low reconstruction error. The filters have flat spectral response at the DC and aliasing frequencies.

Keywords

Chebyshev approximation; graph theory; high-pass filters; signal processing; Chebyshev polynomial approximation; channel filter bank; energy networks; flatness constraints; graph QMF; graph signal processing; high-pass filters; ideal Meyer function; low degree filters; neuronal networks; quadrature mirror filters; reconstruction error; spectral graph theory; transportation networks; undirected graphs; Chebyshev approximation; Filter banks; Kernel; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems (ISCAS), 2015 IEEE International Symposium on

Conference_Location

Lisbon

Type

conf

DOI

10.1109/ISCAS.2015.7169218

Filename

7169218