A new moving average technique with a unique way of assigning weight has been proposed to reduce the influence of the bad/stray data points or large short term fluctuations automatically. A simple iterative technique is introduced wherein the weights of elements are dynamically optimised. This method has been compared with another proposed method which finds the average of a set of data by applying Fuzzy logic through generation of a special membership function. These two methods have been applied on some arbitrarily generated test data for establishing their validation. Finally this technique has been used to smooth the GNSS based timing data. The capabilities of smoothing data utilizing these techniques have been analyzed.
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