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Proceedings ArticleDOI

Design of maximally decimated linear phase orthogonal filter bank using iterative SVD technique and its applications

Sourabh Tonde, +2 more
- Vol. 2016, pp 1340-1343
TLDR
Singular valued decomposition technique is introduced to design Linear Phase Orthogonal filter bank which yields efficient and fast results in time critical applications.
Abstract
Filter Banks traditionally designed by the factorization method which is complex and time consuming. Singular valued decomposition technique is introduced to design Linear Phase Orthogonal filter bank which yields efficient and fast results in time critical applications. Signal splitting and efficient reconstruction of the original signal is studied achieving perfect reconstruction condition due to the orthogonal nature of designed filter bank. Ultimate aim of proposed methodology is to design two approximation scenarios in terms of square matrices which apparently maps into the filter bank matrix. Singular valued decomposition is iteratively employed to compute both of these square matrices until achievable convergence is achieved between to alternate iterations. Proposed algorithm starts with the design of least square filter bank and ends with the filter bank which ensures orthogonality conditions as well as all filters in the filter bank satisfying linear phase condition. Thus, faster design of the filter bank along with linear phase orthogonal condition yields multiple applications in signal processing, image processing, communication etc.

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Citations
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An Improved Type 2 Fuzzy C Means Clustering for MR Brain Image Segmentation Based on Possibilistic Approach and Rough Set Theory

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MS Lesion Segmentation for Single and Multichannel MRI Images Using MICO Technique

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References
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Journal ArticleDOI

Lattice structures for optimal design and robust implementation of two-channel perfect-reconstruction QMF banks

TL;DR: A lattice structure and an algorithm are presented for the design of two-channel QMF (quadrature mirror filter) banks, satisfying a sufficient condition for perfect reconstruction.
Journal ArticleDOI

Linear phase paraunitary filter banks: theory, factorizations and designs

TL;DR: A minimal factorization is developed for a large class of linear phase paraunitary systems in which each individual filter in the analysis synthesis banks has linear phase, and this factorization significantly reduces the number of parameters to be optimized in the design process.
Journal ArticleDOI

Linear-phase perfect reconstruction filter bank: lattice structure, design, and application in image coding

TL;DR: A lattice structure for an M-channel linear-phase perfect reconstruction filter bank (LPPRFB) based on the singular value decomposition (SVD) is introduced, which can be proven to use a minimal number of delay elements and to completely span a large class of LPPRFBs.
Journal ArticleDOI

On factorization of M-channel paraunitary filterbanks

TL;DR: In this paper, the authors investigated the factorization of causal finite impulse response (FIR) paraunitary filterbanks with given filter length, and developed a new structure for the design and implementation of paraunary system based on the decomposition of Hermitian unitary matrices.
Journal ArticleDOI

On M-channel linear phase FIR filter banks and application in image compression

TL;DR: This paper investigates the theory and structure of a large subclass of M-channel linear-phase perfect-reconstruction FIR filter banks-systems with analysis and synthesis filters of length L/sub i/=K/ sub i/M+/spl beta/, and develops a complete and minimal factorization for all even-channellinear-phase paraunitary systems.
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