A cubic B-spline interpolation algorithm that uses the first derivative values of the input function in the knots

Signal interpolation is an old problem that could be resolved by filtering techniques. One dedicated filter is used to determine the coefficients from the input samples and another filter is applied in order to obtain the interpolated values. In this paper is presented a new technique for coefficients determination. The approximation function is a cubic B-spline one. We are presenting the results for signal interpolation by a factor m=2^r. The algorithm is implemented for some well known signals (like sine, cosine and triangle functions) and the results are discussed at the end.