%0 Journal Article %A F. Castillo and J. Arellano and S. Sánchez %D 2010 %J International Journal of Electronics and Communication Engineering %B World Academy of Science, Engineering and Technology %I Open Science Index 39, 2010 %T Statistical Approach to Basis Function Truncation in Digital Interpolation Filters %U https://publications.waset.org/pdf/13816 %V 39 %X In this paper an alternative analysis in the time domain is described and the results of the interpolation process are presented by means of functions that are based on the rule of conditional mathematical expectation and the covariance function. A comparison between the interpolation error caused by low order filters and the classic sinc(t) truncated function is also presented. When fewer samples are used, low-order filters have less error. If the number of samples increases, the sinc(t) type functions are a better alternative. Generally speaking there is an optimal filter for each input signal which depends on the filter length and covariance function of the signal. A novel scheme of work for adaptive interpolation filters is also presented. %P 480 - 484