Discrete optimization of digital filters using Gaussian adaptation and quadratic function minimization

Kjellström, Gregor; Taxén, Lars; Lindberg, Per Olov

doi:10.1109/tcs.1987.1086040

Cited by 5 publications

(1 citation statement)

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“…In digital filter designs there is a similar problem, where the coefficients must be quantized to be represented by finite precision binary words [1,12,17,18,20,37]. However, the problem involving SC filters is fundamentally different.…”

Section: Introductionmentioning

confidence: 99%

Using a Genetic Algorithm to Optimize Capacitance Ratio Approximations in SC Filters

Soares

Filho

Petraglia

2010

Circuits Syst Signal Process

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Accurate capacitance matching is one of the main design issues in switched-capacitor (SC) filters. Using identical unit capacitors in parallel to implement each filter capacitor, combined with a careful layout design, can provide an accuracy of 0.1% in the filter coefficients. The disadvantage of this technique is the fact that it can be directly applied only if the coefficients can be expressed as ratios of integer numbers. As a result, coefficient approximations are required, leading to frequency response errors. In this paper, a genetic algorithm (GA) is used to find the optimum capacitance ratio approximations by rational numbers that minimize the total number of unit capacitors for a given error tolerance in the frequency response. Design examples in 0.35 µm CMOS are presented and simulated to illustrate the proposed approach and verify its effectiveness.

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