TABLE OF CONTENTS In this chapter, we exploit a new way of passive modeling interconnect circuits by so-called signal waveform shaping. Traditional passive modeling methods try to ensure that the reduced models are strictly passive using passive-preserving model order reduction methods or passivity enforcement optimization methods, as shown in Chapter 2 and Chapter 10. In this chapter, we show that passivity can also be achieved by slightly altering (shaping) the waveforms passing through the reduced models.
Many model order reduction (MOR) techniques have been proposed in the past. The most efficient and successful one is based on subspace projection [32, 37, 85, 91, 113], which was pioneered by asymptotic waveform evaluation (AWE) algorithm [91] where explicit moment matching was used to compute dominant poles at low frequencies. After AWE, more numerical stable techniques were proposed [32, 37, 85, 113] by using implicit moment matching and congruence transform to produce passive models. A detailed review of Krylov subspace methods can be found in Chapter 2.
Another important development in linear MOR is the introduction of truncated balanced realization (TBR) methods, where the weak uncontrollable and unobservable state variables are truncated to achieve the reduced models [81, 87, 89, 131]. The TBR methods can produce nearly optimal models but they are more computationally expensive than projection-based methods. Also, TBR can produce passive models in its latest developments [87, 89, 131], which can be approximately viewed as generalized projection-based reduction methods [89]. The TBR methods are reviewed in Chapter 3.
Although projection-based MOR...
