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Complicated mathematical operations are in the heart of any signal processing application and therefore minimization of computational time is one of the major areas of concern at which the researchers have been looking for years. A number of evolutionary optimization techniques have proved their faithful appearance in various signal processing operations, particularly in the field of digital filter design. However, they often require significantly higher time to converge, thus making the approach unsuitable for applications requiring higher throughput. In this paper, an attempt has been made towards the improvement of the convergence nature of a popularly used optimization technique namely, Differential Evolution (DE) through the use of an alternative approach, called Opposition-based Differential Evolution (ODE), derived from the concept of DE in designing low-pass Finite duration Impulse Response (FIR) filter. Performance comparison between these two distinct techniques has been carried out from different analytical angles. Finally, it has been concluded that ODE outperforms DE in every respect as considered in this work.