High-quality causal interpolation for online unidimensional signal processing

We present a procedure for designing interpolation kernels that are adapted to time signals; i.e., they are causal, even though they do not have a finite support. The considered kernels are obtained by digital IIR filtering of a finite support function that has maximum approximation order. We show how to build these kernel starting from the all-pole digital filter and we give some practical design examples.