An Efficient Method of Group Delay Equalization for Digital IIR Filters

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The paper presents the equalization problem of non-linear phase response of digital IIR type filters. An improved analytical method of designing a low-order equalizer is presented. The proposed approach is compared with the original method. The genetic algorithm is presented as an iterative method of optimization. The vector and matrix representation of the all-pass equalizer are shown and introduced to the algorithm. The results are compared with the analytical method. In this paper we have also proposed the use of an aging factor and setting the initial population of the genetic algorithm around the solution provided by the analytical methodology

  • [1] Ziska P., Vrbata J. (2006). Method for design of analog group delay equalizers. Proc. IEEE ISCAS, 445-448.

  • [2] Farhang-Boroujeny B., Nooshfar S. (1991). Adaptive phase equalization using all-pass filters. Proc. IEEEICC, 1403-1407.

  • [3] Umino K., Andersen J., Hove R.G. (1990). A novel IIR filter delay equalizer design approach using a personal computer. Proc. IEEE ISCAS, 1,137-140.

  • [4] Quelhas M.F., Petraglia A. (2003). Group delay equalization of discrete time filters. Proc. IEEE ISIE, 2, 924- 927.

  • [5] Zhang L., Kwasniewski T. (2010). Optimal equalization for reducing the impact of channel group delay distortion on high-speed backplane data transmission. Int. J. of Electron. and Commun., 64(7), 671-681.

  • [6] Piskorowski J., Kaszynski R., Gutierrez de Anda M. A., Sarmiento-Reyes A. (2008) Group delay compensation and settling time minimization in continuous-time elliptic filters. Proc. IEEE MELECON, 12-16.

  • [7] Gupta A., Parsa A., et al., (2010). Group-delay engineered noncommensurate transmission line all-pass network for analog signal processing. IEEE Trans. Microw. Theory Tech., 58(9), 2392-2407.

  • [8] Piskorowski J., Gutierrez de Anda M. A. (2009). A New Class of Continuous-Time Delay-Compensated Parameter-Varying Low-Pass Elliptic Filters With Improved Dynamic Behavior. IEEE Trans. CircuitsSyst. I, Reg. Papers. 56(1), 179-189.

  • [9] Piskorowski J. (2006). Phase-Compensated Time-Varying Butterworth Filters. Analog Integr. CircuitsSignal Process., 47(2), 233-241.

  • [10] Quelhas M.F., Petraglia A. (2005). Initial solution for the optimum design delay equalizers. Proc. IEEEISCAS, 4, 3587-3590.

  • [11] Golonek T., Jantos P., Rutkowski J., (2012). Stimulus with limited band optimization for analogue circuit testing. Metrol. Meas. Syst., 19(1), 73-84.

  • [12] Goldberg D.E., (1989). Genetic Algorithms in Search, Optimization, and Machine Learning. Boston: Addison Wesley.

  • [13] Holland J. (1992). Genetic algorithms. Scientific American. 66-72.

  • [14] C. Coello (June 2005). An updated survey of GA-based multiobjective optimization techniques. ACMComputing Surveys, 32(2), 109-143.

  • [15] Bird J., Layzell P. (2002). The evolved radio and its implications for modeling the evolution of novel sensors. Proceedings of the 2002 Congress on Evolutionary Computation. 1836-1841.

  • [16] Srinivas, M., Patnaik, L.M. (1994). Adaptive probabilities of crossover and mutation in genetic algorithms. IEEE Trans. Syst., Man, Cybern., Syst., 24(4), 656-667.

  • [17] Haupt, R.L. (2000). Optimum population size and mutation rate for a simple real genetic algorithm that optimizes array factors. IEEE APS., 2(2), 1034-1037.

Metrology and Measurement Systems

The Journal of Committee on Metrology and Scientific Instrumentation of Polish Academy of Sciences

Journal Information

IMPACT FACTOR 2016: 1.598

CiteScore 2016: 1.58

SCImago Journal Rank (SJR) 2016: 0.460
Source Normalized Impact per Paper (SNIP) 2016: 1.228


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