An empirical study of evolutionary techniques for multiobjective optimization in engineering design
An empirical study of evolutionary techniques for multiobjective optimization in engineering design
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Efficient signal processing techniques are necessary for assessing the exposure to broadband magnetic fields. The use of flat-top windows along with the DFT is a simple and fast method that reduces the characteristic leakage errors and picket fence effects when using the classical DFT for the exposure assessment. This paper proposes a new class of flat-top windows, making a trade-off between the sidelobe fall-off and the maximum sidelobe height, called fast-decaying minimum-sidelobe (FDMS) flat-top windows. Moreover, the procedure used to find the coefficients of the optimal flat-top windows is reviewed, and a new procedure is proposed in order to find the flat-top window coefficients that uses multi-objective optimization and an appropriate selection of constraints. Using this procedure, a new minimum sidelobe (MS) flat-top window with four terms is also found, having better characteristics than a previously proposed 4-term MS flat-top window. In addition, a new MS flat-top window with five terms is proposed having a maximum sidelobe level of -95.15dB. These windows are used to propose a method for assessing the exposure to broadband magnetic fields using flat-top windows and the DFT.