Abstract
We present a novel implementation strategy for distributed autoregressive moving average (ARMA) graph filters. Differently from the state of the art implementation, the proposed approach has the following benefits: (i) the designed filter coefficients come with stability guarantees, (ii) the linear convergence time can now be controlled by the filter coefficients, and (iii) the stable filter coefficients that approximate a desired frequency response are optimal in a least squares sense. Numerical results show that the proposed implementation outperforms the state of the art distributed infinite impulse response (IIR) graph filters. Further, even at fixed distributed costs, compared with the popular finite impulse response (FIR) filters, at high orders our method achieves tighter low-pass responses, suggesting that it should be preferable in accuracy-demanding applications.
Original language | English |
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Title of host publication | 2017 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings |
Place of Publication | Piscataway, NJ |
Publisher | IEEE |
Pages | 4119-4123 |
Number of pages | 5 |
ISBN (Electronic) | 978-1-5090-4117-6 |
DOIs | |
Publication status | Published - 2017 |
Event | ICASSP 2017: 42nd IEEE International Conference on Acoustics, Speech and Signal Processing - The Internet of Signals - Hilton New Orleans Riverside, New Orleans, LA, United States Duration: 5 Mar 2017 → 9 Mar 2017 Conference number: 42 http://www.ieee-icassp2017.org/ |
Conference
Conference | ICASSP 2017 |
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Abbreviated title | ICASSP |
Country/Territory | United States |
City | New Orleans, LA |
Period | 5/03/17 → 9/03/17 |
Internet address |
Keywords
- autoregressive moving average graph filters
- graph filters
- graph signal processing