DCGA optimization of lowpass FRM IIR digital filters over CSD multiplier coefficient space

Bokhari, Syed; Nowrouzian, B.

doi:10.1109/mwscas.2009.5236029

Cited by 4 publications

(2 citation statements)

References 11 publications

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“…In [21][22][23], a technique was developed for finite-precision design and optimization of FRM digital filters using GAs. finite-precision optimization of FRM FIR digital filters using PSO was studied in [24,25] and finite-precision optimization of infinite impulse response based (IIR-based) FRM digital filters was studied in [26,27].…”

Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimization of Highly Selective Digital Filters over the Finite-Precision Multiplier Coefficient Space

Hashemi¹,

Nowrouzian²

2013

Digital Filters and Signal Processing

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Section: Introductionmentioning

confidence: 99%

Particle Swarm Optimization of Highly Selective Digital Filters over the Finite-Precision Multiplier Coefficient Space

Hashemi¹,

Nowrouzian²

2013

Digital Filters and Signal Processing

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“…Simulated annealing (SA) [8] and genetic algorithms (GAs) [9], [10] have emerged as promising candidates for the design and discrete optimization of digital filters, particularly due to the fact that they are capable of automatically finding near-optimum solutions while keeping the computational complexity of the algorithm at moderate levels. They allow a robust search of the solution space through a parallel search in all directions without any recourse to gradient information.…”

Section: Introductionmentioning

confidence: 99%

A Novel Discrete Particle Swarm Optimization for FRM FIR Digital Filters

Hashemi¹,

Nowrouzian

2012

JCP

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This paper presents a novel discrete particle swarm optimization (PSO) for frequency response masking (FRM) finite impulse response (FIR) digital filters over the canonical signed-digit (CSD) multiplier coefficient space. A look-up table (LUT) scheme is employed to ensure that the PSO automatically searches through permissible CSD multiplier coefficient values in the course of optimization without any recourse to backtracking. This is achieved by searching through the indices of the CSD multiplier coefficient values in the LUT instead of the coefficient values themselves. In this way, the resulting multiplier coefficient values are ensured to conform to a prespecified wordlength as well as to a prespecified maximum number of non-zero digits. The salient feature of this LUT scheme is that by introducing barren layers in the LUT, there is no need to limit the search space manually in the course of PSO to prevent from going over the boundaries of the search space. Examples are given to illustrate the application of the proposed PSO to the design and optimization of a lowpass and a bandpass FRM FIR digital filters

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Recursive digital filter design based on FRM approach

Shen

Lim

2010

2010 Asia Pacific Conference on Postgraduate Research in Microelectronics and Electronics (PrimeAsia)

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DCGA optimization of lowpass FRM IIR digital filters over CSD multiplier coefficient space

Cited by 4 publications

References 11 publications

Particle Swarm Optimization of Highly Selective Digital Filters over the Finite-Precision Multiplier Coefficient Space

Particle Swarm Optimization of Highly Selective Digital Filters over the Finite-Precision Multiplier Coefficient Space

A Novel Discrete Particle Swarm Optimization for FRM FIR Digital Filters

Recursive digital filter design based on FRM approach

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