A more reliable reduction algorithm for behavioral model extraction

In this paper we are concerned with developing more reliable model reduction algorithms. We have focused on less common, but real, examples that fail to be effectively reduced by almost all of the currently popular model reduction methods. The failure of these popular methods is due to the fact that they all separately examine controllability and observability. We then present a new method based on several modifications and extensions of the recently developed AISIAD algorithm. The modified AISAID method is demonstrated on a wide variety of examples, including electrical interconnect, micromachined devices, and heat flow to show that the method is reliable. Our modified AISAID method is either nearly equivalent or far superior to any of the other reduction methods suitable for large scale problems.