Efficient DDD-based term generation algorithm for analog circuit behavioral modeling

An efficient approach to generating symbolic product terms for behavioral modeling of large linear analog circuits is presented. The approach is based on a compact determinant decision diagram (DDD) representation of transfer functions and characteristics of analog circuits. The new algorithm is based on the concept that a dominant term in a DDD graph can be found by searching the shortest path in the graph. But instead of traversing a whole DDD graph each time, we show that a shortest path can be found by just updating a small number of the newly added vertices after the first shortest path is found. Experimental results indicate that the new symbolic term generation algorithm outperforms both pure shortest path based algorithm and dynamic programming based algorithm, which is the fastest symbolic term generation algorithm published so far.