ted. As an example, we mention the computation of an oscillator's impulse sensitivity function by means of HTM-based techniques. The oscillator HTMs involved can be shown to have a rank-degenerate structure. This structure could be exploited to streamline computations. Having established methods that capture linear time-varying behavior, we can proceed by taking time-varying weak nonlinearities into account. Analyzing time-varying weakly-nonlinear behavior builds on perturbation techniques and linear time-varying system analysis. It thereby proceeds along the same lines of reasoning as time-invariant weakly-nonlinear system analysis [Wamb98a]. De- veloping methods for time-varying weakly-nonlinear system analysis would con- tribute yet another step towards a true top-down analysis (and hence design) of electronic systems and circuits. With regard to the analysis of oscillator dynamic behavior, the work above is but the beginning of what promises to become a powerful technique to analyze and model a wide variety of systems: Properly adapted, it is applicable to virtually every system whose behavior is characterized by the presence of widely spaced time constants. Here, it is not re- quired for these systems to be autonomous. In [Vana02e], the theory was adapted to handle, for instance, PLL large-signal behavior. A step that is of major importance to the methods here presented concerns the partitioning of the system equations, i.e. finding the core system. A general- purpose algorithm to do SO would greatly contribute to the flexibility of the method and the scope of its applications. Finally, it would be interesting to explore the link between both oscillator analysis and the HTM framework. As was discussed in chapter 5, projection of the perturbation terms requires us to solve systems of linear DAEs. In many cases, these systems turn out to be periodic. Hence, in principle, they can be handled using HTM-based tech- niques. Appendix A HTM norms and the comparison of HTMs his appendix deals with HTM norms and the c