Digital filters having sharp transition band play a vital role in modern digital signal processing (DSP) applications. Emerging technologies require digital filters to be both computationally efficient in software/hardware realizations. This thesis is concerned with the design and structural-level optimization of sharp transition band digital filters employing the well known frequency response masking (FRM) approach. Unlike the conventional finite impulse response (FIR) based FRM approach, the FRM technique used in this thesis incorporates infinite impulse response (IIR) digital interpolation subfilters, thereby reducing the overall filter order that results in a reduction of hardware complexity. Two realization methods are discussed in this thesis, namely, the bilinear-lossless-discrete-integrators (bilinear-LDI) digital filter design technique, and the lattice wave digital filter (lattice WDF) digital filter design technique.
Diversity controlled (DC) genetic algorithm (GA) is employed to optimize both types of IIR based FRM digital filters over the efficient canonical signed digit (CSD) multiplier coefficient space. DCGAs represent FRM digital filters by a binary chromosome and proceed from a population pool of candidate chromosomes to future generations in order
to arrive at the desired FRM digital filter satisfying the design specifications. A novel cost-function is used that allows the DCGA to simultaneously optimize both the amplitude-frequency and group-delay frequency response. A fast convergence speed has been observed. / Communications
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:AEU.10048/1014 |
| Date | 06 1900 |
| Creators | Bokhari, Syed |
| Contributors | Dr. Behrouz Nowrouzian (Electrical and Computer Engineering), Dr. Ray Nilanjan (Computer Sciences), Dr. Venkata Dinavahi (Electrical and Computer Engineering) |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 1493837 bytes, application/pdf |
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