  This study aims to show the efficiency of a proposed spectral matching
technique for the reduction of required ground motions in the dynamic time
history analysis. In this non-stationary spectral matching approach,
unconstrained optimization is employed to adjust the signal to match a target
spectrum. Adjustment factors of discrete wavelet transform (DWT) coefficients
associated with the signals are then considered as decision variables and the
Levenberg-Marquardt algorithm is employed to find the optimum values of DWT
coefficients. This matching algorithm turns out to be quite effective in the
spectral matching objective, where matching at multiple damping ratios can be
readily achieved. First, the efficiency of the spectral matching procedure is
investigated in a case study earthquake record and then compared with two
conventional spectral matching methods. Results show considerable improvement
in the matching accuracy which is accompanied by minimal changes in shaking
characteristics of the original signal. In addition, it is shown that
earthquake records matched with the proposed method can noticeably reduce the
essential number of ground motions that are normally required for the dynamic
analysis of a case study model. In this regard, it has been found that we can
reduce the number of required motions by more than 80% when matched motions are
selected to be used as the seismic inputs for the dynamic analysis.
