1. A method for predistorting an input signal at a predistorter to compensate for distortion introduced by a non-linear electronic device operating on the input signal to produce an output signal, comprising: generating, for each of a plurality of sampling time instances, first and second signal samples representing said input and output signals, respectively, wherein said first and second signal samples are spaced at unit-delay intervals and wherein each of the second signal samples corresponds in time to one of the first signal samples; calculating, from the first and second signal samples, parameters for an artificial neural network (ANN)-based model that includes a tapped delay line configured to dynamically model memory effects of the distortion introduced by the electronic device, or of a response of the predistorter, with a multi-unit delay interval between at least one pair of adjacent delays, wherein the tapped delay line comprises a variable tapped delay line, and wherein the method further comprises dynamically selecting the multi-unit delay interval between the at least one pair of adjacent delays from a plurality of candidate multi-unit intervals, based on a ratio of the sampling rate of the first and second samples to a nominal baseband bandwidth of the input signal; and predistorting the input signal according to the ANN-based model, to produce a predistorted input signal for input to the electronic device.