Title :
Graph QMF with flatness constraints
Author :
Tay, David B. H. ; Lin, Zhiping
Author_Institution :
Dept. of Electron. Eng., LaTrobe Univ., Bundoora, VIC, Australia
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;
Conference_Titel :
Circuits and Systems (ISCAS), 2015 IEEE International Symposium on
Conference_Location :
Lisbon
DOI :
10.1109/ISCAS.2015.7169218