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This study aims to show the efficiency of a proposed spectral matchingtechnique for the reduction of required ground motions in the dynamic timehistory analysis. In this non-stationary spectral matching approach,unconstrained optimization is employed to adjust the signal to match a targetspectrum. Adjustment factors of discrete wavelet transform (DWT) coefficientsassociated with the signals are then considered as decision variables and theLevenberg-Marquardt algorithm is employed to find the optimum values of DWTcoefficients. This matching algorithm turns out to be quite effective in thespectral matching objective, where matching at multiple damping ratios can bereadily achieved. First, the efficiency of the spectral matching procedure isinvestigated in a case study earthquake record and then compared with twoconventional spectral matching methods. Results show considerable improvementin the matching accuracy which is accompanied by minimal changes in shakingcharacteristics of the original signal. In addition, it is shown thatearthquake records matched with the proposed method can noticeably reduce theessential number of ground motions that are normally required for the dynamicanalysis of a case study model. In this regard, it has been found that we canreduce the number of required motions by more than 80% when matched motions areselected to be used as the seismic inputs for the dynamic analysis.

On the reduction of required motions in the dynamic analysis using an optimization-based spectral matching