Efficient approximation of symbolic network functions using matroid intersection algorithms

An efficient and effective approximation strategy is crucial to the success of symbolic analysis of large analog circuits. In this paper we propose a new approximation strategy for the symbolic analysis of linear circuits in the complex frequency domain. The strategy directly generates common spanning trees of a two-graph in decreasing order of tree admittance product, using matroid intersection algorithms. The strategy reduces the total time for computing an approximate symbolic expression in expanded format to polynomial with respect to the circuit size under the assumption that the number of product terms retained in the final expression is polynomial. Experimental results are clearly superior to those reported in previous works.