Improved techniques are provided for modeling a target Volterra series using an orthogonal parallel Weiner decomposition. A target Volterra Series is modeled by obtaining the target Volterra Series V comprised of a plurality of terms up to degree K; providing a parallel Wiener decomposition representing the target Volterra Series V, wherein the parallel Wiener decomposition is comprised of a plurality of linear filters in series with at least one corresponding static non-linear function, wherein an input signal is applied to the plurality of linear filters and wherein outputs of the non-linear functions are linearly combined to produce an output of the parallel Wiener decomposition; computing a matrix C. for a given degree up to the degree K, wherein a given row of the matrix C corresponds to one of the linear filters and is obtained by enumerating monomial cross-products of coefficients of the corresponding linear filter for the given degree; and determining filter coefficients for at least one of the plurality of linear filters, such that the rows of the matrix C are linearly independent.