z-logo
open-access-imgOpen Access
Impedance matrix compression using effective quadrature filter
Author(s) -
JiunnMing Huang,
JengLong Leou,
ShyhKang Jeng,
JennHwan Tarng
Publication year - 2000
Publication title -
iee proceedings - microwaves antennas and propagation
Language(s) - English
Resource type - Journals
eISSN - 1359-706X
pISSN - 1350-2417
DOI - 10.1049/ip-map:20000361
Subject(s) - quadrature mirror filter , algorithm , wavelet , mathematics , discrete wavelet transform , computer science , filter design , wavelet transform , filter (signal processing) , electronic engineering , artificial intelligence , prototype filter , engineering , computer vision
An effective quadrature mirror filter (QMF) proposed by Vaidyanathan and Huong (1988) has been used to solve 2D scattering problems. QMF has been popular for some time in digital signal processing, under the names of multirate sampling, wavelets, etc. In this work, the impulse response coefficients of QMF were used to construct the wavelet transform matrix. Using the matrix to transform the impedance matrices of 2D scatterers produces highly sparse moment matrices that can be solved efficiently. Such a presentation provides better sparsity than the celebrated and widely used Daubechies wavelets. These QMF coefficients are dependent on the filter parameters such as transition bandwidth and filter length. It was found that the sharper the transition bandwidth, the greater the reduction in nonzero elements of the impedance matrix. It also can be applied in the wavelet packet algorithm to further sparsify the impedance matrix. Numerical examples are given to demonstrate the effectiveness and validity of our finding

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom