Behavioral Modeling of Analog Circuit via SGWD Approximation

In this paper,Shannon-Gabor wavelet distributed approximation functions （SGWD）,which combine Shannon sampling with a Gabor-distributed approximation functional （Gabor-DAF ） window function,are used to construct the behavioral models of analog circuit blocks. Two techniques,periodic extension of the approximated curve and even-symmetrical mirroring of the original transfer function,are proposed to reduce the approximation boundary errors.In the first technique,the approximated function is modified to make the two boundary values equal,and then the modified curve is expanded into a periodic function.In the second algorithm,the approximated curve is expanded by even symmetrical mirroring at the two boundary points.Compared with the classical polynomial approximation method,the proposed methods have less computational complexity and can reach higher accuracy.Some numerical examples are also given to demonstrate the merits of these proposed algorithms.