 write down algorithms in a manner that does not suffer from the ambiguities common to everyday languages like English or Dutch. On the other hand, there is always the need for intu- itive understanding of descriptions written down in some abstract language. Whatever you do, you must always understand what you are doing. Over centuries, mathematics has developed as the mainstream language of science. It is conceived to provide means for a consistent, accurate and quantitative description of our observations of the world around us. Since this text aims at consistency and preciseness in its description of the different topics being treated, it has a highly math- ematical content. For example, the theory of LPTV systems is grounded on concepts of integral equations and functional analysis while oscillator modeling is build on the theory of stable manifolds and averaging. However, the reader should not be deterred by this. It has been tried to clarify all mathematics in this text by means of intuitive (geometrical) interpretations. Especially among engineers, mathematics often has a reputation for getting too ab- stract. Concepts like manifolds and integral equations seem like nice toys for a mathe- matician, but too abstract and complicated to be useful in (circuit) engineering design practice3 This is reinforced by a mathematician's love for abstraction. They carefully avoid physical interpretation. The latter is considered as compromising the universal abstract character of mathematics. However, although abstraction can help linking top- ics as diverse as climate dynamics and oscillator phase noise, it goes past the essence mathematics: a language for describing our "everyday" observations. Every mathemat- ical expression should therefore have meaning to those who read it. It should invoke images and should help us in our quest for intuitive understanding. Decoupling meaning from formalism, semantics from syntax, reduces mathematics to a set of rules for deducing new statements from old ones. One stops wondering w