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University of Windsor

FIR filter design using Jacobian elliptic Sn function with wavelet applications.

Abstract

dc:description.abstract

This thesis presents a new method of digital FIR filter design based on the Jacobian elliptic sine function. In addition to a general design, a special result is obtained for Quadrature Mirror Filters (QMF) for use in multi-resolution filter banks. These are called Quasi-Dyadic FIR filters. Most of the Quasi-Dyadic filter coefficients are alpha2-n , where alpha is the scale of the coefficients and n is a positive integer. With these special coefficients, the 'multiply' operation may be changed to a 'shift' operation in assembly coding in signal filtering. Since 'shift' is much faster than the 'multiply' instruction in most microprocessors or DSP chipsets, the Quasi-Dyadic filter is more efficient. For multi-resolution filter banks (wavelet-like), perfect reconstruction (PR) is shown to be possible by a novel strategy. In addition, simpler structures that do not provide PR are shown to be valuable in practical applications. Implementation on a DSP board is also presented. Source: Masters Abstracts International, Volume: 39-02, page: 0567. Adviser: James Soltis. Thesis (M.A.Sc.)--University of Windsor (Canada), 2000.

Degree

thesis:*
Name thesis:degree_name
M.A.Sc.
Level thesis:degree_level
Masters
Discipline thesis:degree_discipline
Civil and Environmental Engineering
Grantor
University of Windsor
Year dc:date.issued
2000

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Qiu, (John) Zhengluo
Advisor dc:contributor.advisor
  • Soltis, James

Rights

dc:rights
Language dc:language.iso
en_CA

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/20.500.14776/1734
OAI identifier oai:identifier
oai:uwindsor.scholaris.ca:20.500.14776/1734

Chain of custody

source
Harvested from
University of Windsor
Base URL
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Last updated
2026-07-27
Source record
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citation

Qiu, (John) Zhengluo. FIR filter design using Jacobian elliptic Sn function with wavelet applications.. Masters thesis, University of Windsor, 2000. https://hdl.handle.net/20.500.14776/1734