Fast Design of 2D and Double-prototype Fully Oversampled DFT Modulated Filter Banks

JIANG Junzheng; GUO Yun; OUYANG Shan

doi:10.11999/JEIT160125

Volume 38 Issue 11

Dec. 2016

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JIANG Junzheng, GUO Yun, OUYANG Shan. Fast Design of 2D and Double-prototype Fully Oversampled DFT Modulated Filter Banks[J]. Journal of Electronics & Information Technology, 2016, 38(11): 2753-2759. doi: 10.11999/JEIT160125

Citation:

JIANG Junzheng, GUO Yun, OUYANG Shan. Fast Design of 2D and Double-prototype Fully Oversampled DFT Modulated Filter Banks[J]. Journal of Electronics & Information Technology, 2016, 38(11): 2753-2759. doi: 10.11999/JEIT160125

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Fast Design of 2D and Double-prototype Fully Oversampled DFT Modulated Filter Banks

doi: 10.11999/JEIT160125

Funds:

The National Natural Science Foundation of China (61261032, 61371186), The Guangxi Natural Science Foundation (2013GXNSFBA019264)

Received Date: 2016-01-26
Rev Recd Date: 2016-06-20
Publish Date: 2016-11-19

Abstract

Abstract

Traditional design methods of two-dimensional large-scale filter banks suffer from high-complexity. This paper presents an algorithm to design two-dimensional double-prototype fully oversampled Discrete Fourier Transform (DFT) modulated filter bank with Nearly Perfect Reconstruction (NPR). The algorithm is based on bi-iterative scheme, where the design issue is formulated into an unconstrained optimization issue whose objective function is the weighted sum of the transfer distortion and the aliasing distortion of the filter bank, and the stopband energy of the Prototype Filters (PFs). By exploiting the gradient information, the optimization problem can be efficiently solved by utilizing the bi-iterative scheme. The matrix inverse identity and the fast algorithm for Toeplitz-block Toeplitz matrix inversion are employed to dramatically reduce the computational cost of the iterative procedure. The theoretical analysis and numerical experiments are carried out to show that compared with the existing methods, the new algorithm possesses much lower computational cost and can be used to design large-scale two-dimensional filter bank with better overall performance.

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References(18)

References

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