lization of the work (on phase noise analysis) in [Dem00a, Dem00b, Dem02, Kae90]. To the author's knowledge, the theory presented in this chapter is, to a large extent, original. It is grounded onto two major components: Perturbation theory [Kev81, Kha96] provides an elegant framework to model the interactions between an oscillator's core system and a set of perturbation terms. The perturbation analysis here presented extends the projection technique in [Dem00a, Dem00b, Dem02, Kae90] to capture, besides the phase variations, the dynamics of the oscillator's amplitude and common-mode level. It is also able to handle the behavior of systems of coupled oscillators. The analysis results in a set of equations that govern the oscillator's state-changing behavior (see section 5.1.3). It requires proper partitioning of the oscillator circuit equations into a core system and perturbation terms. This work does not address general 5.2.4 Contributions of this work methods to do the partitioning. Instead, it operates on a case by case basis. Note, however, that such a "case" often spans a wide variety of circuits. Averaging allows us to extract the equations that govern the slow-varying com- ponents of the oscillator's state-changes. This work is restricted to the use of first-order averaging transformations. In most cases, this yields results that are sufficiently accurate. The averaging techniques presented in this text adapt the results in [Bogo61, Verhu96] to handle the presence of noise. This allows them to deal with matters like oscillator phase noise. The advantages of this method over other techniques to analyze oscillator dynamic behavior, e.g. plain transient SPICE simulations, are: We are able to exploit the presence of the widely separated time constants (steady- state versus settling behavior) that typically characterize an oscillator's behavior. While this often poses a bottleneck to traditional (SPICE-like) circuit simulation algorithms, it enables the methods presented in this work to explicitly separate the o