Fixed-order H2 and Hinfinity optimal deconvolution filter designs

Abstract For the simplicity of implementation and saving of operation time, the fixed-order optimal deconvolution filter design is appealing for engineers in signal processing from practical design perspective. In this study, a design method based on genetic algorithms is proposed to simultaneously treat with H 2 and H ∞ optimal signal reconstruction design problem with prescribed filter order. Genetic algorithms are optimization and machine learning algorithms, initially inspired from the processes of natural selection and evolutionary genetics. They tend to find the global optimum solution without becoming trapped at local minima. Both IIR and FIR cases are discussed in this study. The convergence property of our design algorithm is also discussed by Markov chain method. Two design examples of H 2 and H ∞ optimal deconvolution with fixed-order filters are given to illustrate the design procedure and the performance of the proposed design methods, respectively.

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