A Novel Method for Designing M-channel BiorthogonalOversampled Graph Filter Banks

JIANG Junzheng; LIU Songliao; OUYANG Shan

doi:10.11999/JEIT170462

Volume 39 Issue 12

Dec. 2017

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Article Navigation > Journal of Electronics & Information Technology > 2017 > 39(12): 2970-2975

JIANG Junzheng, LIU Songliao, OUYANG Shan. A Novel Method for Designing M-channel BiorthogonalOversampled Graph Filter Banks[J]. Journal of Electronics & Information Technology, 2017, 39(12): 2970-2975. doi: 10.11999/JEIT170462

Citation:

JIANG Junzheng, LIU Songliao, OUYANG Shan. A Novel Method for Designing M-channel BiorthogonalOversampled Graph Filter Banks[J]. Journal of Electronics & Information Technology, 2017, 39(12): 2970-2975. doi: 10.11999/JEIT170462

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A Novel Method for Designing M-channel BiorthogonalOversampled Graph Filter Banks

doi: 10.11999/JEIT170462 cstr: 32379.14.JEIT170462

Funds:

The National Natural Science Foundation of China (61261032, 61371186), Innovation Project of GUET Graduate Education (2017YJCX21)

Received Date: 2017-05-16
Rev Recd Date: 2017-08-14
Publish Date: 2017-12-19

Abstract

Abstract

This paper presents an efficient algorithm to design M-channel oversampled graph filter banks with better overall performance. In the new algorithm, a two-step scheme is exploited to tackle the design task. Firstly, for controlling the spectral selectivity, the analysis filter is designed by solving a constraint optimization problem that minimizes the passband ripple and stopband energy subject to 3 dB constraint; secondly, by taking the Perfect Reconstruction (PR) condition into account, the design problem of synthesis filters is formulated into an optimization problem that minimizes the stopband energy subject to PR constraint. Both the optimization problems are Semi-Definite Programming (SDP), which can be efficiently solved. Since the proposed method fully considerate the spectral characteristic and PR condition, M-channel biorthogonal oversampled graph filter banks with better performance can be obtained. Numerical examples and comparison show that compared with the existing methods, the proposed method can lead to graph filter banks with smaller reconstruction error.
- Graph filter bank,
- Oversampled,
- Perfect Reconstruction (PR),
- Semi-Definite Programming (SDP)

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References(16)

References

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